Lord Howe Island Hybrid Renewable Energy Project · Howe Island Hybrid Renewable Energy Project -...

Lord Howe Island Hybrid Renewable Energy Project LORD HOWE ISLAND BOARD

Technical Feasibility Study

Rev | 1

27 March 2015

Lord Howe Island Hybrid Renewable Energy Project Technical Feasibility Study

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Lord Howe Island Hybrid Renewable Energy Project

Project no: RT019500 Document title: Technical Feasibility Study Revision: 1 Date: 27 March 2015 Client name: Lord Howe Island Board Project manager: David Pollington Author: Jessica Sharples and David Pollington File name: C:\Users\DPollington\Documents\300 - Projects\Lord Howe Island\Tech Feas Report\Lord

Howe Island Hybrid Renewable Energy Project - Final 1 300315.docx

Jacobs Group (Australia) Pty Limited ABN 37 001 024 095 100 Melville St, Hobart 7000 GPO Box 1725 Hobart TAS 7001 Australia T +61 3 6221 3711 F +61 3 6221 3766 www.jacobs.com

COPYRIGHT: The concepts and information contained in this document are the property of Jacobs Group (Australia) Pty Limited. Use or copying of this document in whole or in part without the written permission of Jacobs constitutes an infringement of copyright.

Revision Date Description By Review Approved

A 17/03/2015 Draft for client comment

J.Sharples

M.Orpella

D.Pollington

D.Pollington

D.Pollington

0 27/03/2015 Original Issue

J.Sharples

M.Orpella

D.Pollington

D.Pollington

R.Dudley

D.Pollington

1 30/03/2015 Minor Amendments to the Exec Summary D.Pollington

J.Sharples D.Pollington D.Pollington

Acknowledgements

Jacobs would like to acknowledge the assistance provided by the Board in the preparation of this study, in particular Andrew Logan and Greg Higgins for their assistance with the provision of information and providing the site specific knowledge when it was required.

Jacobs would like to thank ABB for their assistance in understanding aspects of their earlier work on the HREP and their assistance with their DIgSILENT models of their battery system. Jacobs would also like to thank Vergnet for their assistance with a range of technical enquiries.


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Contents Executive Summary .........................................................................................................................................1 1. Introduction ..........................................................................................................................................6 2. Scope of this Study ..............................................................................................................................9 3. Study Methodology ............................................................................................................................ 10 4. Previous Work .................................................................................................................................... 12 4.1 Energy Supply Road-Map (2011) .......................................................................................................................................... 12 4.2 Technical Design Specifications (2013) ................................................................................................................................. 12 4.3 ABB Business Case (2013) .................................................................................................................................................. 13 4.4 AECOM Business Case (2014) ............................................................................................................................................. 13 5. Existing LHI Electricity and Fuel Consumption ................................................................................ 14 5.1 Current Load Profile ............................................................................................................................................................. 14 5.1.1 Diurnal and Seasonal Load Profile ........................................................................................................................................ 15 5.1.2 Weekly Load Profile ............................................................................................................................................................. 17 5.1.3 Monthly Energy Production and Maximum Power .................................................................................................................. 18 5.2 Future Load Profile – Loads and Generation ......................................................................................................................... 20 6. Preliminary Design ............................................................................................................................. 21 6.1 HREP RMU and Battery Transformer .................................................................................................................................... 21 6.2 Battery System ..................................................................................................................................................................... 22 6.3 Road .................................................................................................................................................................................... 22 6.4 Solar .................................................................................................................................................................................... 23 6.5 Wind .................................................................................................................................................................................... 25 7. Wind Resource ................................................................................................................................... 27 7.1 Introduction .......................................................................................................................................................................... 27 7.2 Wind Resource Analysis ....................................................................................................................................................... 27 7.2.1 Summary ............................................................................................................................................................................. 27 7.2.2 Site Monitoring Mast Measurement Equipment...................................................................................................................... 28 7.2.3 Onsite Wind Measurements .................................................................................................................................................. 30 7.2.4 Reference Data Selection ..................................................................................................................................................... 33 7.2.5 Reference Data Wind Measurements .................................................................................................................................... 33 7.2.6 Cross Correlation and Data Synthesis ................................................................................................................................... 35 7.2.7 WasP Wind Flow Modelling .................................................................................................................................................. 37 7.2.8 Site Air Density .................................................................................................................................................................... 39 7.3 Wind Energy Yield Analysis .................................................................................................................................................. 39 7.3.1 Summary ............................................................................................................................................................................. 39 7.3.2 Turbine Data ........................................................................................................................................................................ 40 7.3.3 Gross and Net-of-Wake-Losses AEP Calculations ................................................................................................................. 40 7.3.4 Net-of-All-Losses AEP Calculations ...................................................................................................................................... 41 7.3.5 Uncertainty Analysis ............................................................................................................................................................. 41 7.4 Issues Requiring Further Analysis or Clarification .................................................................................................................. 43 8. Solar Resource ................................................................................................................................... 44


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8.1 Introduction .......................................................................................................................................................................... 44 8.2 Solar Resource Analysis ....................................................................................................................................................... 44 8.2.1 Site Solar Measurement Equipment ...................................................................................................................................... 44 8.2.2 Onsite Solar Measurements.................................................................................................................................................. 45 8.2.3 Reference Solar Measurements ............................................................................................................................................ 47 8.2.4 Cross Correlation and Data Synthesis ................................................................................................................................... 48 8.3 Data Validation with Private PV Installations.......................................................................................................................... 50 8.4 Solar Energy Yield Analysis .................................................................................................................................................. 52 8.4.1 Solar PV System Configuration ............................................................................................................................................. 52 8.4.2 Estimated Energy Yield ........................................................................................................................................................ 53 8.5 Issues Requiring Further Analysis or Clarification .................................................................................................................. 55 9. HREP System Modelling .................................................................................................................... 57 9.1 Introduction .......................................................................................................................................................................... 57 9.2 Modelling Specifics ............................................................................................................................................................... 57 9.2.1 275kW Vergnet WTG ........................................................................................................................................................... 57 9.2.2 400kW/400kWh Battery ........................................................................................................................................................ 58 9.2.3 450kWpAC and 550kWpAC LHIB Solar PV ............................................................................................................................... 58 9.2.4 120kWpAC Private Solar PV ................................................................................................................................................... 58 9.2.5 300kW Detroit Series 60 14l Diesel Genset ........................................................................................................................... 58 9.2.6 Load Data ............................................................................................................................................................................ 59 9.2.7 Wind .................................................................................................................................................................................... 59 9.2.8 Solar .................................................................................................................................................................................... 59 9.2.9 Ambient Temperature ........................................................................................................................................................... 59 9.3 Results ................................................................................................................................................................................ 59 9.3.1 Wind Annual Generation ....................................................................................................................................................... 62 9.3.2 LHIB Solar PV Annual Generation ........................................................................................................................................ 62 9.3.3 Private Solar PV Annual Generation ..................................................................................................................................... 62 9.3.4 Diesel Fuel Consumption ...................................................................................................................................................... 63 9.3.5 Renewable Penetration ........................................................................................................................................................ 63 9.4 Further Option for Consideration ........................................................................................................................................... 63 9.5 Fuel Consumption ................................................................................................................................................................ 65 9.6 Diesel Genset Run Hours ..................................................................................................................................................... 66 9.7 Diesel Genset Daily Operation .............................................................................................................................................. 66 10. Potential Equipment Suppliers .......................................................................................................... 70 10.1 Wind Turbines ...................................................................................................................................................................... 70 10.2 Batteries .............................................................................................................................................................................. 70 10.3 Solar Panels ........................................................................................................................................................................ 71 10.4 Control System .................................................................................................................................................................... 71 11. CAPEX and OPEX .............................................................................................................................. 73 11.1 Capital Cost Estimate Review ............................................................................................................................................... 73 11.2 Operational Cost Estimate Review ........................................................................................................................................ 74


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12. Schedule Review ................................................................................................................................ 75 13. Power System Studies ....................................................................................................................... 76 13.1 Steady State Studies ............................................................................................................................................................ 76 13.2 Dynamic Studies .................................................................................................................................................................. 77 14. Protection Study ................................................................................................................................ 80 15. Communications Study ..................................................................................................................... 81 16. Geotechnical Investigations .............................................................................................................. 83 16.1 Basis of Recommendations .................................................................................................................................................. 83 16.2 Earthworks ........................................................................................................................................................................... 83 16.2.1 Excavation Conditions .......................................................................................................................................................... 83 16.2.2 Access Road ........................................................................................................................................................................ 83 16.2.3 Wind Turbines ...................................................................................................................................................................... 84 16.2.4 Solar Panel Arrays ............................................................................................................................................................... 84 16.3 Further Assessment ............................................................................................................................................................. 85 17. Recommendations ............................................................................................................................. 86 18. Conclusions ....................................................................................................................................... 87 19. Bibliography ....................................................................................................................................... 89

Appendix A. Drawings Appendix B. Glossary


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Executive Summary The Lord Howe Island Board (the Board) has engaged Jacobs as the Owners Engineer (OE) for the implementation of its Hybrid Renewable Energy Project (HREP) on the Island. The projects aims are to:

Reduce diesel consumption, which will help reduce future electricity tariff increases caused by fuel cost increases

Reduce the cost of generation which will reduce the recurrent funding requirements from the NSW government

The Board has obtained Australian Renewable Energy Agency (ARENA) and NSW Treasury funding to cover the project capital expenditure (CAPEX). The Board considered two options for the HREP. Option 1 encompasses installing wind turbines and solar PV while Option 2 involves installing only solar PV. Both options include the installation of a battery system. Option 1 provides the greatest diesel reduction and is preferred as it maximises the benefits of the project.

The location proposed for the installation of the wind turbines and solar PV is on the northern half of the island, north of the airport. The site, on a cleared section of Transit Hill, is elevated with north facing slopes which provides favourable characteristics for solar and wind. The site is also in close proximity to the island’s powerhouse.

Jacobs has undertaken this Technical Feasibility Study on behalf of the Board to review the technical feasibility of the two options before proceeding to the tender phase of the project. The study does not reassess the options or consider alternative options. The intent of this body of work is to review the technical constraints of the two options in light of new information which was not previously available.

To determine whether the options were technically feasible, Jacobs followed a systematic process:

Review of previous work

Previous work was performed by Powercorp, ABB and AECOM. The outcome of the work was the development of the two options that are being considered in this body of work.

Review previous work

Gather and analyse site data

Assess the current physical and

electrical design

Review potential equipment suppliers

Calculate wind and solar energy yields

Prepare preliminary designs

Model the power system and

determine diesel savings

Compare the results to the

original Business Case


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The forecast electrical demand is an important aspect of the technical feasibility. The historic electrical demand shows that over the last 10 years, the load has been reducing. Advice from the Board confirmed no planned new load growth is expected and the current demand is expected to remain static for the next 5 years. After this period depending on the success of the HREP the Board may look to increase the load by removing the ban on certain loads and introducing electric cars. The results of the analysis found there was little seasonal difference in the load with slightly higher demand in summer due to the larger number of tourists. There is no significant difference in the load profile for the days of the week and there was a strong diurnal pattern with peak loads in the early evening.


A brief review was undertaken of potential suppliers to assess whether there were likely to be any issues with the supply of plant and equipment. It was clear that the project has attracted a lot of market interest and there is a strong desire from suppliers and engineering organisations to be involved. As a consequence, obtaining suitable plant and equipment and conducting a competitive tender process is not expected to be an issue.


The wind resource assessment was completed based on data recorded at the site. The site dataset is short and it is recommended to recalculate the wind Annual Energy Production (AEP) once a full year of data has been recorded later in 2015.

The wind data was correlated with long term data from the nearby Lord Howe Island Aerodrome met station. The results of the analysis indicate that the site has a good wind resource with average wind speeds at the hub height in the order of 7m/s. This presents in the order of 120kW of generation on average or half the average load on the island. This results in energy yields which were consistent with those in the Business Case (BC).

The calculated wind shear for the site is high and as a result mechanical loads on the turbine could be elevated. Confirmation of the suitability of the preferred wind turbine for the site will be required from the turbine supplier once more site data has been collected.

A study of the solar resource was completed based on site recorded data. Again, the solar dataset is short and it is recommended that this is reviewed once a full year of data has been recorded later in 2015.

The solar data was correlated with long term data from SolarGIS, which is based on satellite information and weather models, to obtain a long term solar dataset for the site monitoring mast location. The correlation between the site data and the SolarGIS data was good; however, the site measured data was consistently lower in energy than the SolarGIS data.

The reason for the lower site measured data is not apparent at this stage but may be due to local effects from sea haze. Further investigation is required.


The previous work carried out by the Board and ABB identified the major components of the system and the general areas in which these would likely be installed. This has been taken a step further with this Technical Feasibility Study and a feasible preliminary design for the physical and electrical arrangements has been determined. The preliminary design was developed with the input of the Board and the practicalities of the arrangements assessed during the site visits. It is expected that some elements of the design may change to suit the specifics of the successful tenderer’s equipment.


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Model the power system and determine diesel savings

The two options were modelled using the Homer software with inputs from the specific wind and solar investigations. A generic solar panel and Li-Ion battery1 were selected for use in the model along with the Vergnet 275kW WTG and diesel genset with performance parameters matching the existing LHI units. Inputs into the model included annual time series datasets of load data, wind speed, solar irradiance and ambient temperature.

This modelling showed that both Option 1 and Option 2 of the HREP are technically feasible. However there are number of aspects that require further investigation to remove unknowns or reduce uncertainty. The study makes a number of recommendations to address these issues, which are listed in Section 17 of this report.

The key results of the system modelling of the two proposed HREP systems are provided in the table below, along with the results from the Business Case for comparison.

HREP System Modelling Key Results

Scenario AECOM

Business Case

Jacobs

Technical Feasibility

Percentage Difference from Business Case

(%)

Option 1

Diesel Fuel Consumption (litres) 173,937 209,487 20

Reduction in Fuel Consumption (%) 70.0 64.2 -8

Renewable Penetration (%) 84.0 60.2 -28

Option 2


Reduction in Fuel Consumption (%) 30.0 34.3 14


Compare the results to the original Business Case

It can be seen from the table above that this study predicts a lower reduction in fuel consumption than the Business Case and also a lower Renewable Penetration percentage. Based on the analysis in this study, the difference in Renewable Penetration and fuel consumption is due to a higher estimate of the Solar PV contributions in the earlier studies. The higher estimate is understandable as there was no site data at the time of those calculations and the current site data is indicating lower solar energy than was assumed previously.

It is clear from the above that Option 1 offers a significantly larger reduction in fuel consumption than Option 2.

A third option of the HREP system was modelled. This system was similar to Option 1 with the exception that the 450kWpAC LHIB Solar PV was removed. This modelling highlighted the significance of the wind contribution to the total renewable generation when compared to the solar PV only case (Option 2). The third option achieved a 47.5% Renewable Penetration and a 53% reduction in fuel consumption, demonstrating that the wind generation component provides by far the greatest contribution to fuel savings.

This however does not mean that solar PV should not be installed. Further analysis of the component sizes, including the battery system size, is recommended at the time of tendering to optimise the system and life cycle cost.

A review of costings showed that the BC allocations were most likely sufficient; however, until the tender process is completed, and firm costings are obtained this will not be certain. The final project completion date

1 The BC did not define a solar panel or battery type.


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(system is fully operational) is likely to be delayed by 3 months principally due to the additional time needed to obtain a longer site data record.

Recommendations

A number of recommendations have been raised throughout this study. A summary of the recommendations resulting from this study are provided below:

Number Recommendation Responsible Party Date for Completion

1 The wind turbine suitability for site will need to be confirmed by the wind turbine supplier

WTG supplier November 2015

2 The calculated wind shear at the site monitoring mast is high and this should be monitored and re-assessed as more data is recorded by the site monitoring mast

Jacobs November 2015

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The length of the site wind data available is short and has increased uncertainty associated with the calculations. The long term wind speed and AEP should be recalculated later in 2015, once a full year of site data is available.


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The synthesised solar site data determined in this study results in a much lower AEP compared to the Business Case and Road-Map. It is recommended to immediately consider installing a second sensor in order to enable a check of the site measurement.

LHI Board April 2015

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Similarly to the wind resource calculations, the length of the site solar dataset is short. As a result it is recommended to perform the calculations again later in 2015, when a full year of site data is available so that all seasons will have been covered.


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The maximum demand of the electrical system is critical for determining the amount of “spinning” reserve required to ensure system stability. There is a discrepancy in relation to the magnitude of the measured peak load at LHI from different data sources. This will need to be investigated further and the actual peak vales determined.


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It is recommended in the future that some optimisation studies are carried out as part of the tender process to balance CAPEX, OPEX, Sustaining CAPEX and potential site constraints that may arise as part of the approvals process.

Jacobs and Tenderers

Tender stages

8 Update the wind and solar input time series datasets used for the Homer modelling when more site data is available for analysis and re-run the Homer models based on the updated datasets.


9 It is recommended that further detailed optimisation analysis is carried out at tender stage and that this analysis includes consideration of the entire life cycle, including disposal.

Jacobs and LHIB Tender stages

10 A requirement of the control system tender should include optionality for predictive control strategies which enable the opportunity to run the HREP system more efficiently.

Control System Tenderer

Tender stages

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The following ARENA Milestone dates are varied

Milestone 5 delay by 3 months to 31 December 2015

Milestone 6 delay by 3 months to 31 March 2016

LHIB July 2015


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Important note about your report

The sole purpose of this report and the associated services performed by Jacobs is to assess the feasibility of the proposed Hybrid Renewable Energy scheme on Lord Howe Island in accordance with the scope of services set out in the contract between Jacobs and the Lord Howe Island Board (the Board). That scope of services, as described in this report, was developed with the Board.

In preparing this report, Jacobs has relied upon, and presumed accurate, any information (or confirmation of the absence thereof) provided by the Board and/or from other sources. Except as otherwise stated in the report, Jacobs has not attempted to verify the accuracy or completeness of any such information. If the information is subsequently determined to be false, inaccurate or incomplete then it is possible that our observations and conclusions as expressed in this report may change.

Jacobs derived the data in this report from information sourced from the Board (if any) and/or available in the public domain at the time or times outlined in this report. The passage of time, manifestation of latent conditions or impacts of future events may require further examination of the project and subsequent data analysis, and re-evaluation of the data, findings, observations and conclusions expressed in this report. Jacobs has prepared this report in accordance with the usual care and thoroughness of the consulting profession, for the sole purpose described above and by reference to applicable standards, guidelines, procedures and practices at the date of issue of this report. For the reasons outlined above, however, no other warranty or guarantee, whether expressed or implied, is made as to the data, observations and findings expressed in this report, to the extent permitted by law.

This report should be read in full and no excerpts are to be taken as representative of the findings. No responsibility is accepted by Jacobs for use of any part of this report in any other context.

This study was conducted on Board supplied information along with data from potential suppliers of equipment. Aspects of the study were impacted by the length of onsite wind and solar data available for analysis. As a result those parts of the study using this data will need to be revisited at a later date when a longer data set is available to verify the initial findings.

This report has been prepared on behalf of, and for the exclusive use of, the Board, and is subject to, and issued in accordance with, the provisions of the contract between Jacobs and the Board. Jacobs accepts no liability or responsibility whatsoever for, or in respect of, any use of, or reliance upon, this report by any third party.


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1. Introduction This Technical Feasibility Study has been prepared at the request of the Lord Howe Island Board (the Board) to assess the technical feasibility of the proposed Hybrid Renewable Energy Project (HREP).

There are two options for the HREP which are currently under consideration, the details of each option are shown in Table 1.1 below along with the Business as usual case which represents the current scenario installed at LHI. The preferred option is Option1 although it is possible that the final installation sizing may vary as a result of ongoing work.

Table 1.1 : LHI HREP Options

Scenario

Wind LHIB Solar Private Solar Battery System Diesel Genset

Number of WTGs

Total Capacity

(kW)

Total Capacity

(kWpAC)

Total Capacity

(kWpAC)

Total Capacity

(kW/kWh)

Total Capacity

(kW)

Business as usual 0 0 0 120 0/0 900

Option 1 2 550 450 120 400/400 900

Option 2 0 0 550 120 400/400 900

Figure 1-1 below shows the location of the proposed development area in the context of the northern region of Lord Howe Island [1].

Figure 1-1 : LHI HREP Development Area

Figure 1-2 shows the proposed LHI wind site layout and its surroundings. Table 1.2 provides additional data including the site monitoring mast and turbine coordinates. The turbine locations in this study are different to those used in earlier work due to physical layout constraints at the site.

Development area


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Figure 1-2 : Lord Howe Island Wind Turbine Layout and Environs

Table 1.2 : Site Coordinates2, Elevation, and Height

Item Easting

(m)

Northing

(m)

Elevation

(mASL)

Height

(mAGL)

Site monitoring mast 507253 6511612 80.1 47.7

Turbine T01 507064 6511667 57.3

55.0 T02 507157 6511661 68.3

The LHI proposed wind farm site is located on the northern half of the island, north of the airport. The site, on a cleared section of Transit Hill, is elevated compared to the surrounding area and slopes downhill from the site monitoring mast location towards the west-northwest. There are mountains located towards the south of the island including Mount Gower, the highest point on the island.

The wind turbine site is within a clearing of woodland and the trees which immediately surround the site are approximately 10 to 12m in height. The WTGs are located on a spur so the base of the trees are below the base of the WTGs by approximately 5m.

The Board has proposed three possible areas for solar development in the vicinity of the powerhouse although one of these, Solar Area B, is the subject of ongoing work with Airservices Australia (ASA) to determine the viability of this option. Generally speaking, these areas are ideal for solar generation as they are located on a north facing hill. Figure 1-3 shows the areas considered for solar generation.

2 Coordinate system GDA 1994 MGA Zone 57.

T01

T02

Site monitoring mast

Powerhouse


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Figure 1-3 : LHIB Solar Development Areas

Solar Area A is approximately 3625 m2 in area. This area is constrained by the ASA site, the new access road to the WTGs, the woodland to the south and also the steepness of the northeast area.

Solar Area B is approximately 3320 m2 in area. This area is also constrained by the ASA site, the new access road to the WTGs and the woodland to the south. This site is also subject to further investigation as it would be installed above the ASA earth mat which extends well beyond the above ground equipment.

Solar Area C is approximately 2920 m2 in area. This area is constrained by the northern bushland, the new access road to the WTGs and also the footprint of the wind turbines when these are lowered down.

Solar Area A

Powerhouse

Solar Area B

Solar Area C


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2. Scope of this Study Jacobs’ scope of work on the Lord Howe Island HREP consists of three progressive phases. Phase 1, a Technical Feasibility Study, assesses the feasibility of Options 1 and 2 as proposed in the 2014 LHI HREP Business Case (BC) prepared by AECOM [2]. Phase 2 assesses procurement strategies and includes further studies necessary to implement the project and Phase 3 involves management of the construction project. This study is intended to satisfy the requirements of Phase 1.

The scope of the Technical Feasibility Study was to review the system arrangement proposed in the pre-feasibility study (conducted by others) in order to determine whether it provided a stable network. It is understood that the proposed arrangement was selected following an assessment of a wide range of renewable energy generation, energy storage and power system control technologies.

Consequently, the scope of the Technical Feasibility Study was to consider only one proposed network structure. Accordingly, it is not an options study and does not assess alternative power generation options or alternative network options. The key elements of the proposed HREP consist of the following equipment to be owned by the Board:

450kWpAC of fixed solar PV

400kW/400kWh battery installation

2 x 275kW Vergnet wind turbines

Demand control system and associated communications network proposed by ABB

Up to 120kWpAC of private roof top solar (to be owned by others)

In carrying out the study, potential areas for improvements in the proposed system were identified and recorded where it was felt that a better outcome could be achieved.

This study provides a summary of a set of studies that were prepared to address specific aspects of Phase 1. These supporting studies are:

Steady State and Dynamic Study – undertaken using DIgSILENT

Protection Study

Communications Study – including details of a proposed small scale trial

In carrying out this study, preliminary design activities were undertaken which are captured in a series of electrical and physical drawings attached in Appendix A along with text in Section 6 on Preliminary Design.

This Technical Feasibility Study also includes a revised high level capital cost budget estimate and schedule estimate which is based on vendor supplied information and recent Jacobs experience.

During the course of the study, a site geotechnical investigation was carried out. A summary of the geotechnical investigation findings is included in this Technical Feasibility Study.

The study is purely a technical study so does not include an assessment of the project’s economics, risk assessment or discussion on procurement methodologies. The risk and procurement strategies are specific activities included in Phase 2 of the work that Jacobs is currently engaged to carry out and will be delivered in separate reports during 2015.


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3. Study Methodology To determine whether the options were technically feasible, Jacobs followed a systematic process as shown in Figure 3-1 below.

Figure 3-1 Technical Feasibility Review Process

The specific tasks that Jacobs undertook in this review process are listed below.:

Review of initial documentation supplied by the Board

Requests for Information (RFIs)

- RFIs on the existing electrical system structure from the Board which is used to:

Build a DIgSILENT model of the existing LHI electricity network

Understand the nature of the grid for the Communication Study Work

Determine appropriate connection arrangements for the HREP elements

- RFIs for data on the existing system performance

- RFIs for detailed performance specifications on the diesel gensets and transformers etc.

- RFIs for data from ABB3 (battery and solar) and Vergnet (WTG) for specific technical details of equipment that has been proposed for the HREP

Physical layout considerations to assess practicalities of proposal

- WTG location to assess if it can be installed and operated

- Area for LHIB Solar PV

- Location and space requirements for the Battery System

3 Whilst ABB has not been selected to supply this equipment their past history with this project and stated intention to bid in the future has meant they

were both well informed on the project requirements and willing to provide the DIgSILENT model information. The same information could potentially have been obtained from other suppliers but would likely have been a much slower process whilst they came up to speed with the project.

Review previous work


Assess the current physical and

electrical design




Model the power system and

determine diesel savings

Compare the results to the

original Business Case


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- Preliminary Road design to assess accessibility issues

Preliminary Design of Electrical arrangements

- Preparation of a Single Line Diagram (SLD)

- Preparation of Protection SLD

System, Communications and Protection Studies

- Complete Steady State System Studies and Communication Studies

- Build the Dynamic DIgSILENT Models for the major components

- Carry out Dynamic Model Simulations

- Complete Protection and System Studies

Geotechnical Investigations

- Undertake Site inspections

- Selected soil samples tested and reporting completed

Wind and Solar Site Data

- Review of site monitoring mast arrangement and site wind and solar site data as it was supplied fortnightly

- Correlate the site data (approximately 3 month’s) with long term data sources for wind and solar

- Build WasP terrain model for wind turbine modelling

- Carry out wind annual energy production assessment for the Vergnet WTGs

- Carry out solar annual energy production assessment for proposed LHIB Solar PV and installed Private Solar PV

- Verify Private Solar PV calculations against actual site data from private installations

HREP Integrated System Review

- Build Homer Model of the existing LHI network and Option 1 and Option 2 scenarios

- Verify the model against existing data on diesel fuel consumption and solar PV production

- Confirm the model against the results obtained from the detailed wind and solar analysis

- Undertake review of HREP Option 1 and 2 to assess % Renewable Penetration and potential fuel Savings

Review of potential suppliers, project costs and project program

Recommendations and Conclusions


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4. Previous Work The review of previous work performed focused on four documents in terms of understanding the basis of the current HREP proposal:

Lord Howe Island Renewable Operations, Energy Supply Road-Map by Powercorp [3]

Lord Howe Island Energy Roadmap Implementation, Technical Design Specifications by ABB [4]

LHI Consult – Business Cases – Plan B by ABB [5]

Lord Howe Island, Renewable Energy Project, Business Case by AECOM [2]

The following sections provide a brief summary of the documents listed above.

4.1 Energy Supply Road-Map (2011)

The Road-Map report prepared in 2011 provides an overview of the different renewable technologies available on the market at the time which may be suitable for installation at LHI along with the various energy management technologies which could be used.

Powercorp (now ABB) has modelled a number of different hybrid renewable options using the Homer software and ranked these according to generation costs. The inputs for the Homer model included:

1) LHI demand data from 2010

2) Wind data from 2000

3) Fuel consumption from 2010

4) Existing powerhouse specifications

The resulting conclusion from the Homer modelling was that two Vergnet wind turbines in conjunction with 200kW of community based solar PV and 200kW of Private Solar PV would be able to produce close to 70% Renewable Penetration.

No site specific solar data had been used as an input to the Homer model for the Road-Map.

Based on the most favourable option, Powercorp went on to outline the cost per kWh of generation of the scheme over future years.

4.2 Technical Design Specifications (2013)

The Technical Design Specifications document prepared by ABB in 2013 (Powercorp team was purchased by ABB) aimed to provide “technical equipment specifications and system design considerations that should be evaluated”.

The specification sets out the requirements of the following:

1) Detailed System Design

2) Solar Power Plant

3) Wind Power Plant

4) Communications System

5) Demand Response System

6) Control Integration System

7) Tariff Structure & Metering System

8) Service and Maintenance Obligations


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4.3 ABB Business Case (2013)

Following on from the Technical Design Specifications document, ABB prepared a Business Case report for the project in 2013. The Business Case report focussed on “Plan B” which refers to modifications from the original proposed system recommendation, particularly focusing on the possible constraints that could affect the operation of the wind turbines.

ABB reported that no new site data had been used in the preparation of their Business Case report, however the document goes on to mention the data that has been modified for their analysis.

ABB recalculated the Base Case as specified in the Road-Map and the other Plan B scenarios based on the updated cost information. The results of these calculations were provided and the conclusions of the document state that the each of the cases considered in the analysis were legitimate Plan B options for the system. The ultimate choice in determining the option to implement was dependent on whether the wind turbines will obtain approval, if capital funding is available and the outcome of the financial modelling.

4.4 AECOM Business Case (2014)

AECOM prepared a separate BC in 2014 which focussed on two specific options. The purpose of the BC was to assess the economic and financial worth of the proposed options for the purposes of obtaining funding from the NSW Government. The two options analysed by AECOM are the Option 1 and Option 2 defined and investigated later on in this study. These options are different to those assessed by ABB in the Technical Design specifications and the Business Case, reflecting a change in approach by the Board.

It was noted in the document that the assessment relied on inputs from the earlier technical assessments completed by ABB. AECOM did not perform their own energy modelling and instead used the results calculated by ABB in preparation of the document. As the exact BC options are not explicitly covered in the earlier works by ABB there must have been additional work carried out by ABB to enable AECOM to complete their model. This is consistent with the notes in the AECOM spreadsheet referring to an updated ABB spreadsheet.

AECOM provided indicative capital and operational costs based on the two options along with the cost savings expected as a result of using less diesel fuel at the powerhouse.

The key values from the AECOM BC are compared with the equivalent results from this Technical Feasibility Study in Section 9.3.


14

5. Existing LHI Electricity and Fuel Consumption The Board provided a selection of historical energy, maximum and minimum demands and diesel fuel consumption data. The data was a mixture of annual, monthly and 1 minute data sets which did not completely cover the same time periods for the different data sets. The data was not complete in some cases; however there was sufficient data available to enable the interpolation of missing data for the purposes of this study if necessary.

The contribution to energy production and use of fuel by the back-up diesel generator was not included in this review as it was deemed to be a minor contribution.

The data was reviewed to get an understanding of the annual seasonal and daily trends and hence if the HREP is likely to be impacted by any of these.

The data was also used to derive an annual load profile for the island suitable for use in the Homer modelling software.

5.1 Current Load Profile

The powerhouse data was provided by the Board in 1 minute time series samples covering the period from April 2005 to October 2012 (inclusive).

The time series data was average into 10 minute intervals and screened the data for valid samples. A number of months of data were missing from the dataset or contained “zero” readings, this data was excluded from the analysis.

In addition to the time series data, also provided was the monthly energy production and fuel usage figures from the powerhouse. This data, along with the time series data, is summarised in Table 5.1.

Table 5.1 : Annual Powerhouse Energy, Mean Power, Fuel Usage and Maximum Power Demand

Year Energy Production

(MWh)

Mean Power4

(kW)

Fuel Usage

(litres)

Maximum Power Demand5

(kW)

2005 2425.7 249.4 743150 -

2006 2468.9 253.5 754450 -

2007 2250.0 249.8 733400 -

2008 2300.6 264.6 697000 -

2009 2290.0 269.3 583450 -

2010 2311.0 262.6 585150 490

2011 2325.6 267.6 585350 467

20126 2277.0 260.0 576250 468

2013 2087.0 - 533200 447

2014 2082.0 - 514500 442

4 The annual mean power has been calculated using the valid time series data. This data covered the period from April 2005 to October 2012 hence

no values were calculated for 2013 and 2014. 5 The annual maximum power demand values have been calculated based on maximum demand meter readings taken at each of Islands

substations. The data covered the period from 2010 to 2014. 6 Monthly data for December 2012 was not available due to the new powerhouse being commissioned; arbitrary values were determined for the

month in order to assess the annual trend of energy production.


15

The load profile based on the information above is depicted in Figure 5-1. The step change in fuel consumption in 2008 was due to the replacement of the diesel generators with the current Detroit engines which are far more fuel efficient.

Figure 5-1 : Lord Howe Island Load Profile

The graph above indicates that there has been an overall decline in energy production at the powerhouse since 2005. The decline from 2012 to 2013 can partly be attributed to the contribution from Private Solar installations on the island7; however this contribution is not expected to account for all of the decrease8. A slight decline has also been observed between 2013 to 2014, the Board has indicated that this could be due to one of the major Lodges on the island being closed for renovations for 8 weeks during winter 2014. There was also a distinct drop in energy production from 2006 to 2007. Whilst the island has had a number of efficiency programs which have seen the replacement of electrical equipment such as old fridges and incandescent lights, this would not explain the magnitude of this drop. The Board was not able to provide any further explanation for the decline and the reason remains unknown based on the information received to date.

The graph shows the maximum power demand declining since 2010 matching the downward trend of the annual energy production. Whilst the trend appears to be there is some conflicting data which indicates greater maximum demands. Further analysis of the demand profile and conformation of the maximum demand will need to be undertaken to complete detailed design activities on the HREP.

5.1.1 Diurnal and Seasonal Load Profile

The valid time series data was sorted into summer and winter periods and then further sorted into hourly bins centred on the hour in order to observe the diurnal variation power demand throughout the day. This information can be seen in Figure 5-2.

7 Private Solar PV installations commenced in 2012 8 Some limited annual production data was obtained for some of the private installations and modelling of the installed PV was also carried out. Refer

to Section 8.3 for further details.

430

440

450

460

470

480

490

500

2050

2100

2150

2200

2250

2300

2350

2400

2450

2500

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Max

imum

Pow

er D

eman

d (k

W)

Ene

rgy

Pro

duct

ion

(MW

h)

Year


16

Figure 5-2 : Diurnal and Seasonal Load Profile

The graph above shows that the power demand is lowest overnight as expected. The demand increases in the morning at around breakfast time and remains fairly constant throughout the daytime until late afternoon. As expected again the demand is at its peak during the evening with a maximum occurring around 18:00 and 19:00 hours.

The separate profiles for the winter and summer diurnal variations do follow the same trend of low demands overnight and high demands early evening, however the demand in winter is consistently lower than the summer demand.

The monthly variation in temperature at LHI was also assessed. The temperature data used in the assessment was recorded by the Lord Howe Island Aerodrome met station data and covered the period from January 2004 to December 2014. The mean monthly temperature, along with the temperature range, is displayed in Figure 5-3 below.

150

170

190

210

230

250

270

290

310

330

350

00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00

Pow

er (

kW)

Hour

Winter Summer


17

Figure 5-3 : Monthly Mean Temperature Variation

Figure 5-3 shows that there is only a small variation in monthly temperatures throughout the year indicating a mild climate. As no electric heating and only a very small amount of or air conditioning is directly connected to the Board Electricity network, the small difference between the winter and summer diurnal curves can possibly be attributed to a greater number of tourists visiting LHI during the summer period and the closure of some accommodation lodges during winter each year.

5.1.2 Weekly Load Profile

Again using the valid time series data, the data was sorted according to the day of the week in order to obtain an understanding of the variation of the load over weekdays and weekends. This can be observed in Figure 5-4 below.

0

5

10

15

20

25

30

35

Tem

pera

ture

(°C

)

Month


18

Figure 5-4 : Weekly Load Profile

The weekly load profile shows that there is no significant variation of load between each day at Lord Howe Island.

5.1.3 Monthly Energy Production and Maximum Power

Figure 5-5 shows the monthly energy production figures provided by the Board.

Figure 5-5 : Monthly Energy Production

240

245

250

255

260

265

270

275

280

Sunday Monday Tuesday Wednesday Thursday Friday Saturday

Pow

er (

kW)

Day

140

150

160

170

180

190

200

210

220

230

240

Ene

rgy

Pro

duct

ion

(MW

h)

Month

Average 2005 2006 2007 2008 2009

2010 2011 2012 2013 2014


19

The graph indicates that the highest production months over the years are consistently January and December with lower production observed during the winter months. The curves for 2013 and 2014 are lower than the previous years which corresponds with the low energy production for those years observed in Figure 5-1.

Figure 5-6 below displays the maximum monthly power demand at the powerhouse.

Figure 5-6 : Monthly Maximum Power Demand

The maximum power output from the powerhouse between 2005 and 2014 was 465kW recorded in August 2011; the average maximum values are shown as the bars. There are however some differences when this data is compared to the 1 minute data which showed a peak in November 2008 of 512kW and the 2011 peak was in September peaking at 490kW. The peak requirements or maximum demand of the system is important for determining the amount of “spinning” reserve required. Given there appears to be a discrepancy in relation to the magnitude of the peak load, this will need to be investigated and the actual peak values determined for the tender process.

Using the 1 minute times series data provided by the Board, the monthly average power demand was calculated, this is provided in Figure 5-7.

350

370

390

410

430

450

470

490

Max

imum

Pow

er (

kW)

Month

Average 2005 2006 2007 2008 2009

2010 2011 2012 2013 2014


20

Figure 5-7 : Monthly Average Power Demand

The monthly averages in the graph above indicate a lower power demand period over the winter months compared to summer, this corresponds with the difference observed in the diurnal variation provided in Figure 5-2 and also fits with the assumption that the summer demand is larger due to the higher number of tourists visiting the island.

5.2 Future Load Profile – Loads and Generation

The current trend for power generation by the Board has clearly been reducing over the period examined. The business as usual scenario expects this decline in energy production to bottom out and remain stable as LHI residents complete the installation of energy saving measures and the approved Private Solar is completed.

The Board advised that depending on the success of the HREP it may be possible that loads which are currently met either by gas or private diesel gensets may be allowed to be connected to the Board electrical system. Loads such as electric stoves and ovens and heat pump systems for cooling and heating are likely to be the main items. There is also the possibility of other connected loads such electric cars which would be ideal given the terrain and distances travelled as well as offering the potential for emergency battery storage when the cars are connected to the electricity grid in the event of an immediate shortfall in the Board generation capacity.

Notwithstanding the possibilities flagged above, the Board advise that the position for business as usual will see at most a 0.5% growth in electrical load over the foreseeable future.

200

210

220

230

240

250

260

270

280

290

300

Ave

rage

Pow

er (

kW)

Month

Average 2005 2006 2007 2008 2009 2010 2011 2012


21

6. Preliminary Design The previous work on the HREP carried out by the Board and ABB identified the major components of the system and the general areas in which these would likely be installed. This has been taken a step further with this Technical Feasibility Study and a feasible preliminary design for the physical and electrical arrangements has been determined. The preliminary design was developed with the input of the Board and the practicalities of the arrangements tested with on the ground inspections. It is expected however that once the project goes to tender that some elements of the design may change to suit the specifics of the successful tenderer’s equipment.

The following constraints and drivers were considered during the preliminary design process:

No clearing of any existing remnant native vegetation, except for road access to the WTG site, thus only developing areas that are currently cleared and used primarily for agriculture

Minimise the impact to the highest value agricultural grazing land, and cropping land

Minimise the reduction in grazing land

Avoidance of low lying areas prone to flooding

Consideration of the ASA assets and their constraints

All connections between equipment to be done underground with the possible exception of the solar panel connections between frames

Transformer sizes and arrangements selected to maximise inter-changeability of equipment in the event of a failure

The island has only a 25 tonne small crane so equipment should be sized accordingly

DC based equipment and associated convertors/inverters are isolated from other equipment via a step up transformer. This should assist in trapping harmonics that might interfere with other equipment.

The standard island voltage ratings were selected wherever possible

Ease of operation and isolation

Minimal disruption to the existing island operation of the electrical network when the system is being constructed

Suitability for various contractual models. Whilst the contracting structure is not discussed in this study, some work in relation to this has been undertaken and considered in the Preliminary design.

Constructed roads will be bitumen seal black top to limit ongoing maintenance from water erosion

In undertaking this work, information on the existing LHI electricity network was collated and a single line diagram was prepared to represent the current state of the electrical network, refer to drawing Appendix A.1. The proposed electrical connection of the HREP into the existing LHI electrical network is shown on the proposed single line drawing, refer to drawing Appendix A.29.

The following sections discuss the physical and electrical details of each of the major elements required for Option 1 HREP. If Option 2 were to proceed instead of Option 1 then the only change to the details below would be the removal of the wind turbine elements.

6.1 HREP RMU and Battery Transformer

In this study it was chosen to break into the existing underground cable connection between the north and south substations which are located just outside of the powerhouse (as shown on the Power Station Proposed Layout drawing, refer to drawing Appendix A.9) and install a new Ring Main Unit (RMU) referred to here as the HREP

9 This arrangement was also used in the preparation of the other studies undertaken by Jacobs. Refer to Sections 13, 0, 15 and 16.


22

RMU, see Figure 6-1 below. The HREP RMU will be installed in a kiosk unit that contains a step up transformer for the battery system the battery system will be connected to this transformer via an underground 415V cable.

Figure 6-1 : LHI Powerhouse HREP RMU and Kiosk and Battery Area Locations

The HREP RMU will be connected to both the north and south substations via new 6.6kV underground cables and to the solar and wind RMU via a single 6.6kV underground cable. This arrangement allows for minimal physical disturbance and outage of the existing electrical system assets whilst construction proceeds.

6.2 Battery System

The battery system which would include the batteries, inverter system, 415V switchgear and possibly a control room for the HREP is to be located outside of the powerhouse as shown on the Power Station Proposed Layout drawing, refer to drawing Appendix A.9 and also to Figure 6-1 above.

Based on reviews of similar battery systems installed, it is expected that it will easily be accommodated in the 15m x 7m space that is available between the powerhouse access road and the fence line. These systems are typically fabricated off-site and transported to site and installed, they may be as simple as modified shipping containers. However given the transport limitations associated with getting to LHI and moving larger items on the island it is expected that the successful tenderer will need to create a modified solution to their typical installation for LHI. It is expected that each of the main elements will be located in separate fire segregated rooms.

6.3 Road

The preliminary design of the road to provide access to the solar panels and the wind turbines is shown in the Proposed Layout drawings, provided in drawings Appendix A.6 and A.7. The road has been designed with a 3.5m wide surface which should be adequate to accommodate the largest vehicles likely to use the road, the island crane and tractor. The curves have been designed with the longest loads in mind which are the transport of wind turbine blades in mind. The route of the road has been positioned above the areas prone to flooding but lower down the slope to minimise impact on the north facing slope which will accommodate the solar panels and with minimal intrusion into the highest valued areas used for cropping.

The slope of the road can be seen in the longitudinal section drawing, refer to drawing Appendix A.8, and in two areas is quite steep with 18% and 16% gradients. While roads this steep are not ideal, it is a function of the

HREP RMU and Kiosk Location

Approximate Battery Location


23

terrain that the road is being built in and the surface will be sealed. Alternative designs were investigated that reduced the first steep section by cutting across the slope earlier, however this severely impacted on the prime solar panel space and so was dismissed given the space for solar panels is at a premium.

6.4 Solar

The proposed overall layout drawings (Appendix A.4 and A.5) show three areas that have been identified for the potential placement of solar PV panels. The preference is to locate all of the solar panels in the area marked Solar Area A, however initial designs carried out using typical panel arrangements could not accommodate enough panels just in this area to achieve the 450kWpAC proposed in the BC Option 1 or the 550 kWpAC for Option 2. The arrangement shown on the overall layout drawing is based on 3 solar panels per frame and incorporates the analysis work in Section 8; this arrangement would require 2220 panels. It is estimated that the Solar Area A space can only carry approximately 1200 of these panels and hence the need for Solar Area B which is estimated to accommodate approximately 1000 panels and or Solar Area C which can accommodate approximately 1000 panels also. The two pictures below, Figure 6-2 and Figure 6-3, show the north facing aspect of Solar Area A.

Figure 6-2 : Looking at Solar Area A from the Powerhouse

Figure 6-3 : Looking from Solar Area A towards the Powerhouse


24

Solar Area C (Figure 6-5 below) is the more difficult site to work on and has the potential for greater shading of the more northern panels shown on the drawing. It is for this reason that Solar Area B (Figure 6-4 below) has been considered as the higher preference. However Solar Area B is also problematic as it is the area occupied by ASA‘s installation earth mat. The earth mat is buried approximately 300mm below the ground and consists of 60mm x 2mm hard drawn copper wires emanating from the centre of the installation in 6° increments and fitted with a driven rod at the end of the buried copper wire. On the surface there is no evidence of the earth mat and the area is used to graze cattle. At the time of writing of this study a process was underway to determine if ASA would allow for the installation of solar panels in this space. If successful then this would be a far preferable location to Solar Area C. If unsuccessful, Area C remains a viable but less preferred option for the solar panels.

Figure 6-4 : Solar Area B: Solar panels cover the entire photograph to within 3m of the ASA Assets

Figure 6-5 : Solar Area C: Solar panels are located approximately in the area enclosed by the white line

The output of the solar panels is inverted to 415V 50Hz in approximately 50kW lots. A 50kW inverter was selected to undertake the analysis; however the choice of the inverter size will ultimately be up to the tenderer whilst adhering to the principles listed above. The output of the inverters is transferred via underground cables to a 415V bus in the solar kiosk where it is transformed to 6.6kV. It is at this point where the WTG 6.6kV output connects onto into the solar RMU and the combined solar and WTG output flows via a 6.6kV cable buried alongside the bottom side of the road around to the battery area and across under the road to the HREP RMU.


25

Buried in the ground along with the 6.6kV cables will be an optical fibre cable to enable SCADA communications to the solar and on to each of the WTGs and the site monitoring mast as well.

The process of maintaining the grass down amongst the panels will need to be resolved as the areas are all currently used for grazing cattle which are likely to be incompatible with typical solar installations.

Whilst the arrangement used is typical with a reasonably high efficiency panel to minimise the foot print, it will be up to the tenderer to determine the most cost effective solution that minimises the foot print when considering the PV panel size and frame arrangement. Given the desire to minimise the impacts on grazing land, consideration should be given in the tender process to arrangements that offer the best yield for the minimal area occupied whilst still remaining simple and with little or no maintenance.

6.5 Wind

The location of the wind turbines as shown on the overall layout drawings (refer to drawings Appendix A.4 and A.5) is lower down the cleared area than was previously envisaged in the earlier work. The space required for each Vergnet WTG in a laid down position is shown on the drawing in outline (the shape that looks a bit like a vase) and cannot be physically accommodated higher up the slope. This is based on the requirements specified by Vergnet in their set out documents (6) and (7). The photograph in Figure 6-6 is a view taken from the approximate location of the site monitoring mast looking down towards the location of T02 and T01 further below that.

Normal practice is to pivot the WTGs in the same direction as the prevailing wind which in this case would mean that the wind turbines would pivot roughly facing downhill. However this would mean that the nacelles would be a considerable distance off the ground and would require scaffolding to be built to reach them for service work to be carried out. This would then negate one of the key differentiators of the Vergnet WTG, hence why the WTGs have been located so that they lay down on the ground facing up slope.

Figure 6-6 : WTG Installation Area

The WTG access road has been located to pass between the tower of T01 and its guy wires and there should sufficient height for the Lord Howe Island crane to pass through this space. However the width of the area available will mean that when T01 is lowered down the blades of T01 will block vehicle access to T02. This is not expected to be a major issue.

Each WTG will be accompanied by a small kiosk transformer raising the output of the WTG from 400V to 6.6kV. The output of T02 will flow along a buried HV cable to T01 kiosk where it will connect into the T01 RMU. The


26

combined output of T01 and T02 will then flow via a 6.6kV cable buried off the side of the road or if necessary in the road with suitable protection down to the solar RMU.

As reported in Section 8, the SCADA communication requirements will be achieved via an optical fibre link from the WTGs and site monitoring mast to the powerhouse via Solar Area A.


27

7. Wind Resource 7.1 Introduction

This section describes the wind resource assessment steps and results that were undertaken as part of this study. Table 7.1 provides key results from the study.

Table 7.1 : Key Results

Turbines

Hub Height Wind Resource Annual Energy Production (MWh/year)10 Net P50 Capacity Factor

(%)

Speed

(m/s)

Weibull k

(-) Prevailing Direction

Gross P50

Net P50

Net P90

(10-year)

Net P90

(1-year)

2 x GEVMP 32 275kW 7.0 2.0 Southeast 1563.5 1419.8 1209.2 1142.4 29.5

The above results have been calculated based on approximately 3 months of site recorded wind data. The results are subject to change following further data recording and analysis.

The Annual Energy Production (AEP) and net Capacity Factor (CF) at the site were calculated assuming that operation of the WTGs was unconstrained.

The long term wind resource at the site monitoring mast was calculated using a Measure-Correlate-Predict (MCP) analysis based on site and reference wind speed and directional distributions for 12 direction sectors.

The short term site data used was recorded during an approximately 3 month period. Normal practice would be to use a longer dataset to perform an MCP analysis, however due to the relatively recent installation of the site monitoring mast a longer dataset is not yet available. A follow up to this wind resource section of the study is recommended to be performed before an investment decision is made later in 2015, and then again in 9 months time, when a full year of measured site data is available.

Eleven years of consistent wind data recorded by the Lord Howe Island Aerodrome met station was procured. This data was then correlated with the concurrent reference and site data, and then applied the sector-specific correlative relationships to the long term (11 year) reference data to obtain synthesised long term wind data at the site monitoring mast.

This synthesised long term wind resource data was extrapolated from the site monitoring mast to the turbine locations at hub height using WasP wind flow modelling software. WasP modelling is considered the industry-standard modelling software for wind resource assessments across the world. Jacobs has been using the WasP wind flow modelling software to perform wind resource assessments for many years. WasP was used to calculate the gross AEP. The product of the wake loss factor and other wind farm loss factors was calculated to obtain the overall wind farm loss factor, and hence the net P50 AEP and Capacity Factor.

An uncertainty analysis was performed to assess how the AEP changed with the probability of exceedance (PoE) for different time periods to obtain the net P90 AEP.

7.2 Wind Resource Analysis

7.2.1 Summary

Table 7.2 summarises key results from the wind resource analysis. The values are all annual means taken from WasP tab files. Values at the turbines have been extrapolated from the site monitoring mast using WasP wind

10 P50 AEP represents the energy that is expected to be achieved or exceeded with a likelihood of 50% in an average year. P90 AEP represents the energy that is expected to be achieved or exceeded with a likelihood of 90% in an average year.


28

flow modelling. Short term refers to the concurrent period where data was recorded by both the site monitoring mast and the met station, from 14 November 2014 to 11 February 2015.

Table 7.2 : Key Results from the Wind Resource Analysis

Item Short term Measured

Short term Synthesised11

Long term Measured

Long term Synthesised

Turbines

55.0 mAGL

Wind speed (m/s) - - - 7.0

Weibull k (-) - - - 2.0

Prevailing direction - - - Southeast

Site monitoring mast

47.7 mAGL

Wind speed (m/s) 7.1 7.4 - 7.4

Weibull k (-) 2.6 2.7 - 2.0

Prevailing direction Southeast Southeast - Southeast

Reference data

10.0 mAGL

Wind speed (m/s) 5.5 - 5.7 -

Weibull k (-) 2.4 - 1.9 -

Prevailing direction East - East -

These values were calculated using a Measure-Correlate-Predict (MCP) analysis together with WasP wind flow modelling. This process essentially involved:

Measure site wind data: This data included the 10 minute mean and standard deviation of wind speed and direction measured by anemometers and wind vanes installed at different heights on the 47.7m tall onsite monitoring mast for the period 14 November 2014 to 11 February 2015.

Correlate site data with reference data: This step established relationships between concurrent wind data recorded by the site monitoring mast and that recorded by the nearby Lord Howe Island Aerodrome met station for 12 wind direction sectors [6].

Predict the long term site monitoring mast wind data: This step used the correlative relationships between the site monitoring mast and reference wind data. These relationships were combined with long term historical reference data to predict the wind resource experienced at the site monitoring mast over that same period. Assuming the wind resource over the next such period is statistically similar to that over the historical period provides the predicted long term future wind resource at the site monitoring mast.

Extrapolate long term wind data to the turbines: WasP wind flow modelling software was used to extrapolate the long term site monitoring mast wind data (as calculated above) across the site to the proposed turbine locations at hub height.

Separately, the short term measured site wind data was used to calculate the short term wind shear and turbulence intensity (TI) at the site monitoring mast. This gave a wind shear alpha value of = 0.41, and a TI value at 47.7mAGL for a 15m/s 10 minute mean wind speed of TI15 = 12.8%. These values are considered to be high and further investigation is recommended. The results were shared with Vergnet who concurred that the values were high and may drive the use of a 30m rotor rather than the 32m, but that a longer data set is required to make any firm judgement.

The following sections describe this work in more detail.

7.2.2 Site Monitoring Mast Measurement Equipment

The site is equipped with a 47.7m tall wind monitoring mast. The Board supplied data recorded by this monitoring mast and with data on the mast installation and set-up.

11 The synthesised data has been obtained by applying the calculated correlation parameters determined in the MCP analysis to the corresponding

short term or long term reference data.


29

The onsite monitoring mast is located at GDA 1994 MGA Zone 57 grid reference (507253, 6511612). The mast location is close to the proposed turbine locations and in similar terrain so appears as representative as possible, without obstructing the future WTGs.

Figure 7-1 : Site Monitoring Mast Directional Photographs

The monitoring mast configuration data showed that the mast broadly complies with IEC recommendations [7] which will keep the uncertainty associated with the wind speed measurements to a low level.

The site monitoring mast was equipped with the wind sensors specified in Table 7.3. This table assigns an identifying tag to each sensor which is used (where appropriate) for the remainder of this study.

N

W E

S


30

Table 7.3 : Onsite Monitoring Mast Wind Measurement Equipment

Equipment Tag Make Model Serial Number Height

(mAGL)

Boom Orientation12

(°)

Boom Length (mm)

Arm Length

(mm)

Anemometer A1 WindSensor P2546A 17434 47.7 155 1075 1170





Wind vane WV1 Vector W200P 60345/CV45 37.9 334 1475 1160

Wind vane WV2 Vector W200P 60346/CV46 10.8 334 1475 1160

The anemometers were MEASNET calibrated before the monitoring campaign began. The Board supplied the calibration certificates, with the relevant parameters summarised in Table 7.4. These settings were programmed into the site data logger and so already applied to the data.

Table 7.4 : Anemometer Calibration Parameters

Equipment Tag

Pre-Monitoring Calibration Parameter

Slope

(m/s per Hz)

Offset

(m/s)

A1 0.62104 0.21066

A2 0.62139 0.20600

A3 0.62154 0.20057

A4 0.62124 0.19899

A5 0.62199 0.19641

7.2.3 Onsite Wind Measurements

The Board supplied almost 3 months of wind data recorded by the onsite monitoring mast. This data included the 10 minute mean and standard deviation of wind speed and direction measured from 00:00 on 14 November 2014 to 23:50 on 11 February 2015.

7.2.3.1 Data Availability

The data coverage and sample validity were checked to obtain the overall data availability13.

Table 7.5 summarises the missing, erroneous, and/or suspicious data samples.

12 The boom orientations in this table, and the wind direction in the data, have been recorded to true north (to match the WAsP model and optimise

the wake loss calculations). For this site true north is 14.0º east of magnetic north. 13 ‘Data coverage’ refers to the proportion of samples recorded; ‘sample validity’ refers to all instruments simultaneously providing valid data; data

availability is the product of ‘data coverage’ and ‘sample validity’.


31

Table 7.5 : Missing, Erroneous and/or Suspicious Data Samples

Sample (inclusive) Comment Action

All data WV1 and WV2 disagree WV1 assumed correct

02 Jan 2015 08:10 Missing data sample Missing sample was noted

21 Jan 2015 07:50 Missing data sample Missing sample was noted

Of the 12,960 samples that should have been recorded based on the measurement period duration and the sampling frequency, 12,958 were available. This gave a data coverage of 99.98% which rounds to 100.0%.

Next, the recorded site data was screened to assess sample validity. The data was screened for:

Error values (e.g. N/A, -999, etc)

Whether data is within/outside reasonable limits (e.g. temperature, battery voltage, speed)

Suspicious trends (e.g. constant values or sudden changes)

Instrument agreement/disagreement

Suspicious data was flagged for investigation, and retained or discarded as appropriate.

Data screening revealed a discrepancy between the two wind vanes throughout the entire measurement period. On investigation it was discovered that WV2 may have been experiencing turbulent wind effects due to the trees surrounding the site. With no practicable way to reconcile the two vanes, it was assumed that WV1 was correct. However, this disagreement will increase the uncertainty associated with wind speed (speed up effects, screening) and wind farm efficiency (wake losses).

The sample validity for the measurement period was 100.0%. When combined with data coverage this gave overall data availability of 100.0%. This cleaned site data for the period 00:00 on 14 November 2014 to 23:50 on 11 February 2015 was used for the MCP analysis.

7.2.3.2 Wind Speed and Direction

To eliminate the impact of tower shadow, the speed data from the two top anemometers was merged into a single data file. The data from the upwind anemometer was retained by referring to the uppermost (and hence primary) WV1 wind vane; A1 data was used when 65° WV1 direction < 245° and A2 data otherwise. This gave the site data sample used in the MCP analysis.

For the short term period from 14 November 2014 to 11 February 2015 the mean wind speed at 47.7mAGL was 7.1 m/s.

Figure 7-2 provides the site wind speed and directional distributions.


32

Figure 7-2 : Measured Short Term Site Monitoring Mast Wind Speed and Directional Distributions (A1/A2, WV1)

7.2.3.3 Turbulence Intensity

The measured short term site data was used to calculate the mean turbulence intensity (TI) at the site monitoring mast at 47.7mAGL. Figure 7-3 shows the results using data for all wind directions. The Class limits shown in Figure 7-3 are based on the IEC 61400-1 Standard [8].

Figure 7-3 : Turbulence Intensity at Measurement Height (A1/A2)

The 10 minute mean all-direction TI for 15m/s wind speeds was TI15 = 12.8% which is below the Class B limit as defined in the IEC Standard. The turbine suitability for site will need to be confirmed by the turbine supplier when more site data has been recorded.

0 5 10 15 20 250

10

20

30

40

50Site TIIEC - Class AIEC - Class BIEC - Class CSite TI per wind speed bin

Wind speed (m/s)

Turb

ulen

ce in

tens

ity (%

)

mean_TI_15

15


33

7.2.3.4 Wind Shear

A curve was fitted through the mean wind speeds recorded by the site monitoring mast’s anemometers at different heights. This curve was used to calculate the wind shear alpha value, namely = 0.41. This wind shear exceeds the normal IEC turbine design limit of = 0.20 however it is only based on a short period of data and will be recalculated as further data is recorded. Again, no site classification has been performed and turbine suitability for site should be confirmed with the turbine supplier.

7.2.3.5 Diurnal Analysis

The measured short term site data was sorted into hourly bins centred on the hour in order to observe the diurnal variation of wind speeds experienced at the site monitoring mast throughout the day. Figure 7-4 displays this data.

Figure 7-4 : Diurnal Site Wind Speed Variation

The graph above indicates that the wind speeds over the recording period are slightly higher during the night compared with those recorded in the day. However the variation is small and a more defined diurnal pattern may be observed as further data is recorded by the site monitoring mast.

7.2.4 Reference Data Selection

A number of sources were considered to use as the reference data for the long term correlation. The analysis indicated that the Australian Bureau of Meteorology’s Lord Howe Island Aerodrome met station provided the most suitable data for further analysis.

The met station is approximately 1.3 km south of the site monitoring mast location and is situated at an elevation of 3mASL. The terrain between the site monitoring mast and the met station location is complex and will have an effect on the uncertainty associated with the correlation. The met station is located south of the airport runway and has reasonable exposure, and provides a sufficiently consistent long term data set. This reference data was also available up to the time of analysis so provided the largest amount of concurrent data required for correlation with the site monitoring mast.

7.2.5 Reference Data Wind Measurements

Lord Howe Island Aerodrome met station data was purchased from the Australian Bureau of Meteorology in the form of time series wind speed and direction data. Data from 20 July 1994 to 11 February 2015 was provided, though only data from January 2004 to December 2014 inclusive was used as the long term data for the MCP analysis as prior to 2004 only hourly data was available. In order to maximise the number of samples available for the MCP analysis it was opted to correlate half hourly data samples, hence why the data prior to 2004 was not used as part of the long term dataset. This provided 11 years of data without seasonal bias [6].

0 2 4 6 8 10 12 14 16 18 20 22 246.8

7

7.2

7.4

7.6

Hour

Win

d sp

eed

(m/s

)


34

The time series wind speed and direction data for the Lord Howe Island Aero met station comprised one 10 minute mean sample per half hour. The reference wind speeds were rounded to the nearest km/hour and the wind direction to the nearest 10°. This data was screened and the errors in wind speed and direction were removed.

The mean reference wind speed at 10mAGL for this long term (11 year) period was 5.7m/s and the corresponding data availability was 94.4%.

The short term time series wind speed and direction data for the Lord Howe Island Aerodrome met station was also analysed. This comprised of the period from 14 November 2014 to 11 February 2015 during which site data was also available (the ‘concurrent period’).

The data availability for the short term period from 14 November 2014 to 11 February 2015 was 98.8% and the corresponding mean wind speed was 5.5m/s. This cleaned short term reference data was used in the MCP analysis.

Figure 7-5 and Figure 7-6 show the measured wind distributions at the Lord Howe Island Aerodrome met station for the short term concurrent and long term periods respectively.

Figure 7-5 : Measured Short Term Reference Wind Speed and Directional Distributions (10mAGL)


35

Figure 7-6 : Measured Long Term Reference Wind Speed and Directional Distributions (10mAGL)

7.2.5.1 Reference Data Diurnal Analysis

The long term reference data was sorted into hourly bins centred on the hour in order to observe the diurnal variation of wind speeds experienced at the met station throughout the day. Figure 7-4 displays this data.

Figure 7-7 : Diurnal Reference Wind Speed Variation

The diurnal pattern from the reference wind data shows that the highest wind speeds are experienced in the middle of the daytime, with the peak occurring at 13:00. Overnight the wind speeds are lower with a minimum at 06:00 in the morning. Again the magnitude of the variation in the diurnal trace of the reference wind speeds is small and also that the diurnal effect experienced at the reference met station and the site monitoring mast locations could be different due to the different terrain in which each mast is located.

7.2.6 Cross Correlation and Data Synthesis

The reference and site data recorded between 14 November 2014 and 11 February 2015 was time matched. This provided a total of 4,262 time-matched samples comprising one 10 minute mean once per half hour to establish the correlative relationships.

The short term measured site data used in the cross correlation had a mean wind speed of 7.3m/s at 47.7 mAGL. The equivalent reference data gave a mean speed of 5.5m/s at 10mAGL at the met station location.

0 2 4 6 8 10 12 14 16 18 20 22 245.4

5.6

5.8

6

6.2

Hour

Win

d sp

eed

(m/s

)


36

A 12-sector Weibull curve correlation methodology was used to establish relationships between the site and reference wind speed distributions. Unlike traditional linear regression analyses which establish relationships based solely on instantaneous wind speed, the Weibull curve correlation methodology is based on the wind speed and its associated spread as per the set of IEC61400 Standards. This yields more representative results that better reflect the relationship between the site and reference environments.

The Weibull parameters for the reference and site monitoring mast locations were determined for each direction sector. This was done using a specially developed optimisation process that minimises the differences in energy production, mean wind speed cubed, and mean wind speed associated with the synthesised and measured site data.

The wind roses for the concurrent period show that the prevailing winds at the site came from the southeast and at the reference location from the east. To address this, a directional correlation between the site and reference wind data was performed to obtain a relationship between the two. The reference wind direction was used as the ‘reference direction’, thereby allowing synthesis of the site direction from the long term reference data.

Table 7.6 shows the parameters used and the results in the form of the corresponding bin directions, number of samples, mean wind speeds (U), and Weibull scale (A) and shape (k) parameters. The size and limits of the site directional bins have been optimised to match the fixed bin widths used for the reference data. Bin directions are based on true north.

Table 7.6 : Weibull Correlation Results

Reference Data Bins Site Data Bins Reference Data Site Data

Star

t (°)

Mid

(°)

End

(°)

Sam

ples

Star

t (°)

Mid

(°)

End

(°)

Sam

ples

U (m

/s)

A (m

/s)

k (-)

U (m

/s)

A (m

/s)

k (-)

345 0 15 215 342 351 1 400 3.6 4.1 3.3 8.1 9.0 3.6

15 30 45 554 1 17 32 417 5.6 6.3 2.9 9.1 10.3 3.7

45 60 75 774 32 58 83 798 6.7 7.4 3.6 7.8 8.7 3.1

75 90 105 1028 83 109 134 1036 7.0 7.8 3.5 6.8 7.6 2.6

105 120 135 386 134 135 136 52 3.7 4.2 2.8 7.2 8.1 2.9

135 150 165 147 136 147 157 348 2.9 3.2 3.0 6.5 7.2 2.1

165 180 195 86 157 167 176 130 3.3 3.7 2.2 4.4 5.0 3.6

195 210 225 228 176 193 209 288 4.3 4.8 2.9 6.5 7.4 2.5

225 240 255 265 209 232 255 266 5.3 6.0 2.5 6.7 7.8 2.4

255 270 285 198 255 276 296 192 5.2 5.8 2.6 6.8 7.6 2.7

285 300 315 170 296 307 319 144 3.8 4.2 3.4 7.2 7.9 3.3

315 330 345 211 319 330 342 191 3.9 4.3 3.8 7.5 8.3 3.7

The correlative relationships were applied to the long term reference data to predict the long term wind resource at the site monitoring mast, yielding the results shown in Figure 7-8. The long term synthesised wind speed at the site monitoring mast was 7.4m/s at 47.7mAGL and the wind had a prevailing south-easterly direction.


37

Figure 7-8 : Synthesised Long Term Site Monitoring Mast Wind Speed and Directional Distributions (47.7mAGL)

7.2.7 WasP Wind Flow Modelling

The site is surrounded by some steep terrain and there are trees in the vicinity of the turbine locations which may affect the wind flow at the site. The general site wind flow may not be laminar14 and thus suitability for WasP modelling could be a concern; however the site monitoring mast is located in the same terrain with the same shading effects as the proposed wind turbine locations and therefore WasP15 was determined to be suitable to calculate the wind flow across the site. The analysis in this section of the study is for the indicative, unconstrained annual energy production case and is not considered as a bankable study due to the limitation in the amount of site data available at the time of preparing the study.

WasP is a computer simulation that models physical elements affecting wind flow between a reference site (i.e. the site monitoring mast) and potential wind turbine locations within the same wind climate. WasP modelling reflects local topography, surface roughness, the effect of buildings and atmospheric stability close to the ground. WasP uses the log law to calculate the change in wind speed with height above ground level and hence to extrapolate between site monitoring mast and turbine hub heights. WasP can also combine relevant input data with turbine-specific data to calculate wind farm wake losses and annual energy production before other factors, for example turbine availability and wind farm electrical losses, are taken into account.

The predicted long term wind speed and directional distribution at the onsite monitoring mast (shown in Figure 7-8) was used as the starting point for the WasP wind flow analysis.

Figure 7-9 shows the WasP topography and roughness length model that was used for the wind flow analysis. This map was created by combining data available from topographic and raster maps with data from aerial photographs. The total modelling area is centred on the site and covers approximately 6.4km x 8.4km. Table 7.7 shows the roughness lengths used.

14 WAsP assumes laminar flow in which wind flows over the site in smooth, parallel layers. This is appropriate for flat, open terrain but in increasingly

complex terrain (steep slopes, rocky outcrops, many obstacles, etc) with turbulent and/or recirculating flow the risk of inaccurate WAsP results increases.

15 WAsP version 11.02.0062


38

Figure 7-9 : WasP Topography and Roughness Length Models

Table 7.7 : Roughness Lengths Used in WasP

Terrain Surface Characteristics Roughness Length

(m)

Forest 0.80

Suburbs 0.50

Many trees and/or bushes 0.20

Water (required value) 0.00

Table 7.8 gives the WasP calculated wind resource parameters at the proposed turbine locations. These values, and the energy yield data calculated from them in Section 7.3, are a function of the turbine positions and their surroundings. These values could change if turbines are micro-sited and/or if surroundings alter.

Table 7.8 : WasP Wind Resource Results

Turbine Easting

(m)

Northing

(m)

Height

(mAGL)

Wind Speed

(m/s)

A

(m/s)

k

(-)

T01 507064 6511667 55.0 6.9 7.8 2.0

T02 507157 6511661 55.0 7.2 8.1 2.0

MEAN 507110 6511664 55.0 7.0 8.0 2.0

Figure 7-10 shows net AEP roses (yellow) for each turbine and the wake losses (red). These roses ‘point into the wind’ and illustrate the contribution of each wind directional sector. Wake losses represent the energy that is lost at a WTG due to it being located downwind from another WTG. Upwind turbines are exposed to the full power that is available in the wind whereas downwind turbines (turbines in the wake of others) will be exposed to lower power. Wake losses are dependent on wind direction. T01 experiences the higher wake losses at the


39

LHI site due to T02 being located to the east and a large proportion of the wind is expected to come from that direction. Vice versa T02 experiences the majority of its wake losses when the wind is coming from the west due to the westerly position of T01, however as the proportion of the wind coming from the west is expected to be low the wake losses predicted at T02 are lower than those at T01.

Figure 7-10 : WasP AEP and Wake Loss Roses

7.2.8 Site Air Density

The local site air density at hub height was calculated using elevation data, long term temperature data from the Lord Howe Island Aerodrome met station from January 2004 to December 2014, and standard lapse rate assumptions16. Using a mean elevation of 62.8mASL plus the 55.0mAGL hub height and an estimated mean annual temperature of 19.9°C, a site-specific mean annual hub height air density of = 1.189kg/m3 was obtained. This is 2.9% lower than the standard reference air density of 1.225kg/m3 and hence, for a given wind speed, will result in less wind energy. This is not considered to be significant in the scheme of the project and adjustments to the power curve to account for the lower air density are discussed in Section 7.3.2.

7.3 Wind Energy Yield Analysis

7.3.1 Summary

Table 7.9 summarises the key results from the unconstrained wind energy yield analysis for the Lord Howe Island site.

16 Air density decreases as temperature increases (air expands) and/or as elevation increases (atmospheric pressure falls). Standard lapse rate

assumptions relate to how pressure falls with elevation.


40

0 10 20 300

100

200

300

0

0.2

0.4

0.6

0.8

Unadjusted power curveSite specific power curveThrust curve

Wind speed (m/s)

Pow

er (k

W)

Thru

st c

oeff

icie

nt

Table 7.9 : Key Energy Yield Results

Layout P50 AEP (MWh/year) Net P90 AEP (MWh/year) Net P50 Capacity

Factor

(%) Gross Net 10-year 1-year

2 x GEVMP 32 275kW 1563.5 1419.8 1209.2 1142.4 29.5

These results are derived from the site wind resource data and WasP model described in Section 7.2. WasP was used together with the proposed turbine locations, turbine power and thrust curves, and wind farm losses to calculate the gross AEP and the AEP net of all losses. An uncertainty analysis was then performed to calculate how the AEP changes with the Probability of Exceedance (PoE).

7.3.2 Turbine Data

The AEP was calculated using Vergnet-supplied turbine power [9] and thrust (Ct) curves [10] as per the turbine locations provided in Table 1.2. Table 7.10 provides key turbine parameters. The site-specific power curve in Figure 7-11 was obtained by correcting the unadjusted reference power curve ( = 1.225kg/m3) for the calculated mean site air density ( = 1.189kg/m3) at hub height. The difference between the two curves is small.

Table 7.10 : Key Turbine Parameters

Turbine Type Capacity

(kW)

Hub Height

(mAGL)

Rotor Diameter

(m)

Vergnet GEVMP 275.0 55.0 32.0

Figure 7-11 : Reference and Site-Specific Turbine Power and Thrust Curves

7.3.3 Gross and Net-of-Wake-Losses AEP Calculations

The WasP model was used together with the proposed turbine dimensions, and turbine power and thrust curves to calculate the gross AEP and the AEP net of wake losses. Table 7.11 provides the results on a per-turbine basis.

Wind Speed(m/s)

Reference Power Curve

(kW)

Site Power Curve(kW)

Ct

1 0 0 0.0002 0 0 0.0003 0 0 0.0004 3 3 0.9345 18 17 0.8556 36 35 0.7767 58 56 0.6978 98 95 0.8609 141 137 0.80110 189 184 0.74211 243 237 0.59712 272 270 0.45113 275 275 0.37114 275 275 0.29015 275 275 0.21016 275 275 0.18017 275 275 0.15018 275 275 0.12119 275 275 0.10620 275 275 0.09221 275 275 0.07622 275 275 0.06623 275 275 0.05724 275 275 0.05025 275 275 0.044


41

Table 7.11 : WasP AEP per Turbine Results

Turbine Gross AEP

(MWh/year)

Net-of-Wake AEP

(MWh/year)

Wake Loss Factor

(-)

T01 755.9 726.8 0.961

T02 807.6 792.3 0.981

TOTAL 1563.5 1519.0 0.972

MEAN 781.8 759.5 -

7.3.4 Net-of-All-Losses AEP Calculations

The results in Table 7.11 were used to calculate the net-of-all-losses (NoA) P50 AEP and the corresponding capacity factor. This was done by applying the loss factors set out in Table 7.12 below which are based on typical data from similarly-sized operational wind farms. The analysis has been performed without any sector management or grid constraints applied to the turbines.

Table 7.12 : Other Wind Farm Loss Factors

Item Loss Factor

(-) Comments

Turbine availability (scheduled maintenance) 0.993 Assumed 60h/year

Turbine availability (unscheduled maintenance) 0.970 Assumed

Power curve degradation 0.990 Assumed

Electrical losses 0.980 Assumed

Grid downtime 1.000 Assumed

Grid cap curtailment 1.000 Assumed no grid cap

Noise curtailment 1.000 Assumed no noise curtailment

At the time of writing this study no other factors were known – for example shadow flicker, temperature, planning, and/or environmental constraints – that would affect site energy yield. Depending on the outcome of the ongoing analysis of sea bird movements through the site, there may be some WTG curtailment during small periods of the evening during the breeding season of November to April. However this has not been considered as part of this study and therefore it has been assumed that no such factors apply.

Table 7.13 summarises the results, and also displays the corresponding WasP calculated gross and net site AEPs and capacity factors.

Table 7.13 : The Net-of-All-Losses P50 AEPs and Capacity Factors

Layout Loss Factors (-) P50 AEP (MWh/year) Net P50 Capacity

Factor

(%) Wake Other Overall Gross Net

2 x GEVMP 32 275kW 0.972 0.935 0.908 1563.5 1419.8 29.5

7.3.5 Uncertainty Analysis

The uncertainty analysis is used to quantify how the site AEP changes with the Probability of Exceedance (PoE). The uncertainty assumptions presented in Table 7.14 were used as inputs for this analysis. These values are based on a mix of calculated and estimated site-specific and general parameters. For each parameter, the uncertainty is the standard deviation of what are assumed to be Gaussian distributions expressed as a percentage.


42

For this study the uncertainty analysis has been investigated briefly using typical values. These values will be reassessed once more data from the site monitoring mast is available later in 2015.

The uncertainties are divided into wind resource and energy uncertainties. The wind resource uncertainties and the energy uncertainties are linked by calculating the sensitivity of the yield to the wind speed at the site. For the Lord Howe Island site, a 1.0% wind speed uncertainty corresponds to a 1.9% energy yield uncertainty.

Although the input data used in this study has been analysed it has not been verified. As such, and in line with standard industry practice, data verification uncertainties have not been included in the PoE calculations.

Table 7.14 : Uncertainty Assumptions

Item Value

(%) Comment

Wind Resource Uncertainties

Inter-annual wind speed variability 5.4 / n Based on 5.4% inter-annual variability for 1-year period

Used to calculate the uncertainty over n-year time periods (here n = 1, 5, 10, 15 and 20 years)

Long term wind speed uncertainty 1.6 Based on 5.4% inter-annual variability for 1-year period

5.4%/ 11 years (reference data length)

Site monitoring mast measurement uncertainty

2.5

Estimate

MEASNET calibrated anemometers

Wind vane disagreement imposes wind speed uncertainty (speed up effects, screening)

Site extrapolation uncertainty 4.6

Estimate based on calculations in WasP

Horizontal extrapolation across the site (dRIX = -0.4%)

Vertical extrapolation from 47.7mAGL to hub height

Energy Uncertainties

Correlation uncertainty 2.8

Calculated using concurrent site and reference data. Short term correlative relationship assumed to be similar to long term correlative relationship, e.g. no change in obstacles or roughness at the site and met station.

Power curve uncertainty 1.0 Standard Jacobs assumption

Wind farm efficiency uncertainty 1.2 Standard Jacobs assumption is 1.0%. However, wind vane disagreement imposes extra wake loss uncertainty.

Table 7.15 shows the resulting total standard energy yield uncertainties for 1, 5, 10, 15 and 20 year time periods.

Table 7.15 : Total Standard Energy Uncertainty for Different Periods

Period 1 Year 5 Year 10 Year 15 Year 20 Year

Uncertainty 15.3% 12.0% 11.6% 11.4% 11.3%

Figure 7-12 shows the relationship between the PoE and net AEP based on the P50 net AEP and the total standard uncertainty for different periods.


43

Figure 7-12 : Net AEP as a Function of the PoE

7.4 Issues Requiring Further Analysis or Clarification

The issues relating to the wind resource study that require further analysis or clarifications are:

1) The wind turbine suitability for site will need to be confirmed by the wind turbine supplier

2) The calculated wind shear at the site monitoring mast is high and this should be monitored and re-assessed as more data is recorded by the site monitoring mast

3) The length of the site wind data available is short and has increased uncertainty associated with the calculations. The long term wind speed and AEP should be recalculated later in 2015, once a full year of site data is available.

1 Year 5 Year 10 Year 15 Year 20 Year

50% 1419.8 1419.8 1419.8 1419.8 1419.8

55% 1392.6 1398.4 1399.2 1399.5 1399.6

60% 1365.0 1376.5 1378.2 1378.8 1379.1

65% 1336.4 1354.0 1356.5 1357.4 1357.8

70% 1306.3 1330.2 1333.7 1334.8 1335.4

75% 1273.8 1304.6 1309.0 1310.5 1311.3

80% 1237.7 1276.0 1281.5 1283.4 1284.4

85% 1195.5 1242.7 1249.5 1251.8 1253.0

90% 1142.4 1200.8 1209.2 1212.1 1213.6

95% 1063.8 1138.7 1149.5 1153.2 1155.1

Net AEP (MWh/y)PoE

0.4 0.5 0.6 0.7 0.8 0.9 1800

1000

1200

1400

1-year PoE5-year PoE10-year PoE15-year PoE20-year PoE

Probability of ExceedanceA

EP (M

Wh/

year

)

AEPave

0.5


44

8. Solar Resource 8.1 Introduction

This section describes the solar assessment steps that were undertaken in this study.

It describes the onsite solar monitoring equipment and provides details on the data recorded during the monitoring campaign. As this data covers a rather short period, it has been correlated with a long term solar irradiance data from SolarGIS which is based on satellite information and weather models. The resulting data is expected to be representative of the long term solar irradiance at Lord Howe Island.

The synthesised long term solar irradiance data was used to calculate the expected solar energy production using PVSyst for the Board proposed 450kWpAC and 550kWpAC solar PV installations (LHIB Solar) as well as for the existing 81kWpAC and approved total of 120kWpAC of Private Solar PV. For comparison purposes with the Road-Map study [3], calculations with the unmodified SolarGIS data itself (which is comparable to the NASA derived data used in previous studies) were also undertaken.

8.2 Solar Resource Analysis

8.2.1 Site Solar Measurement Equipment

Solar Global Horizontal Irradiance (GHI17) data has been recorded using a Hukseflux SR12 pyranometer installed on a horizontal boom at 2m above ground level. The Board supplied data recorded by this instrument along with a mast installation and set-up report. The site monitoring mast is located on an elevated area approximately 200m to 300m away from the prospective solar sites. Figure 8-1 shows the base of mast and pyranometer.

Figure 8-1 : Site Monitoring Mast Base and Pyranometer

The main characteristics of the SR12 pyranometer are provided in Table 8.1.

17 GHI is comprised of the direct and diffused components and represents the sum of the incident irradiance. With this parameter it is possible to

recalculate on an arbitrary oriented plane and it provides a direct relation with the energy production in PV systems.


45

Table 8.1 : Pyranometer Characteristics

Item Characteristic

Serial number 1230

Classification First Class (ISO 9060)

Good quality (WMO-No.8)

Calibration date 26 June 2014

Sensitivity (from calibration) 24.98 x 10-6 V/(W/m2)

Uncertainty 1.4%

The sensor was installed and commissioned by Measurement Engineering Australia (MEA) on 13 November 2014.

The pyranometer was installed facing north. The Board site staff confirmed on 19 February 2015 that the sensor was level and the surface was completely clean.

8.2.2 Onsite Solar Measurements

The Board supplied almost 3 months of solar data recorded by the onsite monitoring mast. This data included the 10 minute mean and maximum GHI measured from 00:10 on 14 November 2014 to 09:10 on 13 February 2015.

8.2.2.1 Data Availability

The data coverage and sample validity was checked to obtain the overall data availability18.

Of the 13,159 samples that should have been recorded based on the measurement period duration and the sampling frequency, 13,157 were available. This gave a data coverage of 99.98% which rounds to 100.0%.

Data was scanned and no suspicious values of the 10-mininute mean GHI were found. One suspicious value of the maximum GHI was found, however maximum GHI data was not used in the analysis and so this suspicious sample was ignored.

The sample validity for the measurement period was 100.0%. When combined with data coverage this gave overall data availability of 100.0%. This cleaned site data for the period 00:10 on 14 November 2014 to 10:00 on 01 February 2015 was used for the MCP analysis19.

8.2.2.2 Global Horizontal Irradiance and Insolation

Insolation is comprised of the direct and diffused components of the solar radiation and represents the sum of the incident irradiance in a defined time period (minutes, hours, days, months or years). Most commonly it is defined as global insolation on a horizontal surface and is represented as a long term average in a defined time period (energy/area).

Based on the irradiance (power) recorded by the pyranometer, the monthly global insolation (energy) during the monitoring period has been calculated and is provided in Table 8.2.

18 ‘Data coverage’ refers to the proportion of samples recorded; ‘sample validity’ refers to all instruments simultaneously providing valid data; data

availability is the product of ‘data coverage’ and ‘sample validity’. 19 At the time of analysis, long term data was available until 01 February 2015 only.


46

Table 8.2 : Monthly Insolation

Month Insolation

(kWh/m2)

November 2014 (from 14 Nov) 86.6

December 2014 138.9

January 2015 151.2

February 2015 (up to 13 Feb) 61.2

8.2.2.3 Diurnal Analysis

The measured short term site data was sorted into hourly bins centred on the hour in order to observe the diurnal variation of solar irradiance experienced at the site monitoring mast throughout the day. Figure 8-2 displays the highest, average and lowest hourly average recorded from 14 November 2014 to 13 February 2015.

Figure 8-2 : Diurnal Site Solar Irradiance Variation

The measured irradiance at midday is below what is expected at the latitude of 31° south, which should be in excess of 1000W/m2. This could mean that either there is a problem with the sensor or that there is a localised effect at the LHI site (for example fine layers of haze at the site or mist from sea spray) resulting in lower than expected irradiance measurements.

MEA (the monitoring mast and sensor provider) were contacted who confirmed that the logger had been programmed correctly. Site staff on LHI have also confirmed that the sensor is level and the surface is clean.

In an attempt to determine if the site measurements are a true representation of the solar irradiance experienced at LHI, replication the generation of LHI’s private PV installations was attempted. This analysis is explained in Section 8.3. However the results are inconclusive, for some PV installations the satellite irradiance data is closer to the reported production whereas for other PV installations the production is better represented by the site measured irradiance.

For the above reasons it is recommended that a second sensor is installed to enable a check of the site measurements.

0 4 8 12 16 20 240

500

1000

1500MaximumAverageMinimum

Hour

Sola

r Irr

adia

nce

(W/m

2)


47

8.2.3 Reference Solar Measurements

A number of sources to use as the reference data for the long term solar correlation were considered.

There are no long term ground solar measurements on LHI. The closest long term ground solar measurements available have been recorded by an Australian Bureau of Meteorology met station at Port Macquarie. While the solar data from the Port Macquarie met station was in good order, the correlation between it and the LHI site data was very weak and therefore not suitable for use as the reference solar data.

The only remaining option was to use long term solar data derived from satellite images and weather models. While this data provides a good indication of the solar resource, it carries an inherent error and also may not account for localised factors.

There are several sources of satellite data, some available on the public domain and some available for purchase. Several resources were analysed and SolarGIS20 was selected as it was regarded as one of the most accurate databases and produced hourly data up to 01 February 2015.

The spatial resolution of the SolarGIS data is based on several input data resolutions:

Aerosols (atmosphere): approximately 85 and 125km

Water vapour (atmosphere): approximately 22 and 35km

Satellite data (clouds): approximately 3.5km

Digital terrain model: approximately 250km

The end resolution of the SolarGIS data is close to 3.5km in terms of cloudiness and the uncertainty is reported to be 4.0% on an annual basis.

The SolarGIS data was compared with NASA data (which was used to validate the solar data used in the Road-Map [3]) and the annual energy was found to differ by 9%. This difference is not surprising as the SolarGIS has a higher resolution and also incorporates more atmospheric parameters than the NASA model. The mean monthly insolation for each dataset can be seen in Figure 8-3, noting that the measurement period for each dataset is not the same as the NASA data is unavailable after 2005.

20 The SolarGIS database is a high resolution database recognised as one of the most reliable and accurate source of solar resource information.

The database resides on about 100 terabytes of data and it is updated on daily basis. The data is calculated using in-house developed algorithms that process satellite imagery and atmospheric and geographical inputs (http://solargis.info/).


48

Figure 8-3 : Comparison of SolarGIS and NASA Solar Data

SolarGIS hourly solar irradiance data from July 2006 to January 2015 was used as the reference data for the correlation.

8.2.4 Cross Correlation and Data Synthesis

In order to establish the relationship between the site and the reference data, a correlation between the time-matched measured site irradiance values and the SolarGIS data was performed.

The data used for the correlation covered the period from 14 November 2014 to 01 February 2015 as no more recent SolarGIS data was available at the time of the analysis. The site data was averaged on an hourly basis in order to compare it with the SolarGIS data. Figure 8-4 provides a visual representation of the time-matched data from 14 November 2014 to 22 November 2014.

0

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NASA-SSE (Jul 1983 - Jun 2005) SolarGIS (Jul 2006 - Jan 2015)


49

Figure 8-4 : Hourly Site and SolarGIS Time Series Irradiance Data

In the graph above it can be seen that the site data is consistently lower than the concurrent SolarGIS data. As explained earlier in the study, this could mean that either there is a problem with the sensor or that there is a localised effect occurring at the LHI site such as fine layers of haze or mist from sea spray.

Based on 1,907 time-matched data samples obtained a correlation coefficient (R2) of 94.9% was obtained which denotes a very strong relationship. The gradient of the linear fit through the data is found to be 0.76 which indicates that the site data is approximately 24% lower than what SolarGIS is estimating. The scatter plot and linear fit are presented in Figure 8-5.

Figure 8-5 : Site and SolarGIS Irradiance Correlation

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1200

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/m2 )

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This correlation has been undertaken based on less than 3 months of site data. It is recommended to perform the calculations again later in 2015, when a full year of site data is available so that all seasons will have been covered.

The correlative relationship was applied to the long term reference data to predict the long term site irradiance values. The monthly mean insolation figures for the long term synthesised site data, together with the input SolarGIS data, are presented in Table 8.3.

Table 8.3 : Long term Monthly Insolation Results

Month SolarGIS Insolation

(kWh/m2)

Site Synthesised Insolation

(kWh/m2)

January 203.6 154.1

February 164.8 124.7

March 155.1 117.4

April 112.2 84.9

May 95.0 71.9

June 69.2 52.4

July 80.8 61.1

August 106.7 80.8

September 137.0 103.8

October 173.7 131.5

November 183.7 139.1

December 196.4 148.6

TOTAL 1678.2 1270.4

8.3 Data Validation with Private PV Installations

In an attempt to validate the site measurements, the energy that would have been produced by the existing private PV installations was modelled and compared them to the actual production figures recorded by the individual meters.

The Board supplied the solar energy production readings from February 2014 to February 2015 as well as the installed capacity, commissioning date and panel orientation for 21 private PV installations. The installations ranged from 2kWp to 10kWp. The energy was calculated at only 17 of these 21 installations as these particular sites contained production data for the complete year.

The input solar resource was based on satellite measurements (SolarGIS) correlated with site data for the period February 2014 to February 2015, as well as satellite data uncorrected for the same period.

The analysis has been performed using Pvsyst assuming standard losses (for all systems equal). The actual orientation of each installation has been used, however the tilt was not available and as such 15° tilt was assumed at all installations. Panels are the same but inverters have been sized for each installation.

Three installations (PV 9, 10 and 16) were excluded from the analysis as their results appeared to differ greatly from the other installations. The energy generated at each installation together with the predictions using the SolarGIS and site correlated data are presented in Figure 8-6.


51

Figure 8-6 : Private PV Installations Generated and Predicted Energy February 2014 to February 2015

As it can be seen in the graph above, the calculated energy production using the site correlated solar data comes very close to equalling the actual generation at 8 installations but under predicts the energy at the other 6 installations.

Figure 8-7 presents the deviation between the modelled energy production and actual energy production for both the SolarGIS data and the site synthesised data.

Figure 8-7 : Private PV Installations Predicted Energy Deviation

0

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-50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50%

PV 1 (2kWp)

PV 2 (2kWp)

PV 3 (3kWp)

PV 4 (3kWp)

PV 5 (3kWp)

PV 6 (3kWp)

PV 7 (3kWp)

PV 8 (3kWp)

PV 11 (4kWp)

PV 12 (4kWp)

PV 13 (5kWp)

PV 14 (5kWp)

PV 15 (5kWp)

PV 17 (10kWp)

Energy Deviation

Inst

alla

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Site Synthesised Data Prediction SolarGIS Data Prediction


52

The average energy deviation is 23% for the SolarGIS data and -9% for the site synthesised data respectively. Whilst this seems to confirm the predicted lower generation for the site correlated data, the results are deemed to be inconclusive in terms of proving the site solar data. A longer site data record and a backup sensor on the met mast recording concurrently with the existing sensor is required.

8.4 Solar Energy Yield Analysis

8.4.1 Solar PV System Configuration

8.4.1.1 LHIB Solar Configuration

In order to achieve the required power at the output of the inverters, a higher installed DC capacity is needed in order to account for system losses (system performance ratio).

The system performance ratio was found to be 0.81 based on standard losses and a mid-range efficiency panel used for the LHIB Solar. This means that in order to achieve 450kWpAC at the output, approximately 555kWpDC will be required to install, and to achieve 550kWpAC at the output approximately 679kWpDC is required.

The proposed system is as follows:

Fixed axis technology – tilt of 30°

Orientation (azimuth) – north

PV module – Canadian Solar silicon monocrystalline 250Wp

- 2220 panels with 3 units stacked horizontally on a frame to achieve 450kWpAC

- 2716 panels with 3 units stacked horizontally on a frame to achieve 550kWpAC

Inverter – Hyundai 50kWAC

- 9 units for 450kWpAC


Based on the chosen panel, an active area of 3773m2 is required (without taking into account array separation) for the 450kWpAC solar option and 4620m2 for the 550kWpAC option.

The panel and inverter selection (both size and manufacturer) is not exclusive. The proposed system is purely intended to give an indication of the available energy generation.

8.4.1.2 Private Solar Configuration

The energy contribution from the Private Solar installations on LHI was also modelled. Currently 81kWpAC of Private Solar is installed and operational on LHI, and this is planned to increase to a total of 120kWpAC of Private Solar in the future. Based on standard losses and a typical mid-range panel for private installations, the system performance ratio was calculated as 0.77.

The proposed private system was configured with the following parameters:

Fixed axis technology – tilt of 15°

Orientation (azimuth) – north

PV module – REC silicon polycrystalline 245Wp

- 429 panels to achieve 81kWpAC

- 630 panels to achieve 120kWpAC

Inverter – SMA SUN KING 5000 5kWAC



53


8.4.2 Estimated Energy Yield

Based on the synthesised data and the system configurations presented in the previous sections, the expected energy yield was calculated using the Pvsyst software, version 5.64.

The following assumptions were used in the energy evaluation process:

The albedo (energy yield from reflected light) of surrounding areas used for calculation of yield from reflections from surrounding areas has been assumed to be 20% (reflected from grass)

Based on the preliminary layout, the mutual shading between panels has been modelled as a 0.4-0.6% loss in Pvsyst

The system has been modelled without shading by obstacles in the surrounds and clear horizon

Soiling loss (soiling of modules due to dirt or salt accumulation) is assumed to be 1%. The area is low on dust levels and no high salt accumulation is expected (site staff confirmed that the surface of the sensor was still clean after 3 months of monitoring)

Thermal loss factor 29W/m2K (assumed for free mounted modules with air circulation)

DC cabling ohmic loss (cabling between the panels) is assumed to be 2%

Module quality loss has been assumed to be 0.1% (standard assumption of Pvsyst)

Mismatch loss (these losses are related to the fact that the real modules in the array do not rigorously present the same I/V characteristics) is assumed to be 2% (standard assumption of Pvsyst)

Inverter loss is calculated by the model based on the module specifications

AC losses associated with a step-up transformer (if required) have not been considered

Availability of the plant: 100% based on maintenance being performed during non-daylight hours

The above assumptions were also used to model the Private Solar energies except:

Thermal loss factor 20W/m2K (semi-integrated panels with air duct behind)

DC cabling ohmic loss (cabling between the panels) is assumed to be 3%

The proposed system and constraints described above were used to calculate the expected AEP for the various solar PV options. A summary of the AEPs based on the site synthesised data and the SolarGIS data is provided in Table 8.4. These AEPs do not include losses due to PV panel degradation over time.

Table 8.4 : Solar Energy Yield Results

Layout Capacity

(kWpAC)

Site Synthesised Data AEP

(MWh/year)

SolarGIS Reference Data AEP

(MWh/year)

LHIB Solar Option 1 450 600.7 832.2

LHIB Solar Option 2 550 735.4 1018.8

Current Private Solar 81 108.9 159.7

Planned Private Solar 120 145.2 213.1

The monthly average energy breakdown for the LHIB Solar is presented in Table 8.5.


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Table 8.5 : Monthly LHIB Solar Energy Production

Month

Long term Site Synthesised Data Long term SolarGIS Reference Data

Insolation

(kWh/m2)

Option 1 Energy

450kWpAC

(MWh)

Option 2 Energy

550kWpAC

(MWh)

Insolation

(kWh/m2)

Option 1 Energy

450kWpAC

(MWh)

Option 2 Energy

550kWpAC

(MWh)

January 153.1 63.8 78.1 202.3 82.8 101.4

February 122.6 53.5 65.4 162.0 71.3 87.3

March 118.2 56.4 69.0 156.1 78.0 95.5

April 85.0 43.4 53.2 112.3 63.0 77.2

May 71.6 40.5 49.6 94.6 61.0 74.7

June 53.6 29.9 36.6 70.8 46.5 56.9

July 62.0 34.6 42.4 81.9 53.0 64.9

August 81.2 44.0 53.9 107.3 64.5 78.9

September 104.1 51.9 63.6 137.6 72.7 89.0

October 128.7 59.9 73.4 170.0 80.0 97.9

November 137.2 58.4 71.5 181.3 76.1 93.2

December 156.2 64.4 78.8 206.4 83.2 101.9

TOTAL 1273.6 600.7 735.4 1682.4 832.2 1018.8

The monthly average energy breakdown for the Private Solar is provided in Table 8.6 below.


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Table 8.6 : Monthly Private Solar Energy Production

Month

Long term Site Synthesised Data Long term SolarGIS Reference Data

Insolation

(kWh/m2)

Current Energy

81kWpAC

(MWh)

Planned Energy

120kWpAC

(MWh)

Insolation

(kWh/m2)

Current Energy

81kWpAC

(MWh)

Planned Energy

120kWpAC

(MWh)

January 153.1 12.2 17.9 202.3 15.7 23.0

February 122.6 10.0 14.6 162.0 13.0 19.0

March 118.2 10.1 14.9 156.1 13.5 19.8

April 85.0 7.6 11.1 112.3 10.4 15.3

May 71.6 6.8 10.0 94.6 9.6 14.1

June 53.6 5.1 7.4 70.8 7.3 10.7

July 62.0 5.9 8.6 81.9 8.4 12.3

August 81.2 7.6 11.1 107.3 10.4 15.3

September 104.1 9.3 13.6 137.6 12.4 18.3

October 128.7 11.0 16.1 170.0 14.4 21.1

November 137.2 11.1 16.3 181.3 14.3 21.0

December 156.2 12.4 18.2 206.4 15.9 23.3

TOTAL 1273.6 108.9 159.7 1682.4 145.2 213.1

The rated power output of solar panels typically degrades at about 0.5% per year. In an analytical review of NREL21, some more specific degrading factors are presented depending on the panel composition. As a conservative approach, 0.5% was used as a degradation percentage of power output, applied this to individual years and presented an average on 5 year intervals. The expected energy for the lifetime of the solar installation is shown in Table 8.7.

Table 8.7 : Future Annual Solar Energy Production

Years Efficiency Due to PV

Degradation

(%)

Site Synthesised Data SolarGIS Reference Data

Option 1 Energy

450kWpAC

(MWh)

Option 2 Energy

550kWpAC

(MWh)

Option 1 Energy

450kWpAC

(MWh)

Option 2 Energy

550kWpAC

(MWh)

1 to 5 98.5 591.7 724.4 819.7 1003.5

6 to 10 96.0 576.7 706.0 798.9 978.1

10 to 15 93.5 561.6 687.6 778.1 952.6

16 to 20 91.0 546.6 669.3 757.3 927.1

21 to 25 88.5 531.6 650.9 736.5 901.6

The degradation of the Private Solar has not been modelled, however the degradation is expected to follow a similar trend to the LHIB Solar as described above.

8.5 Issues Requiring Further Analysis or Clarification 1) The solar site synthesised data results in a much lower AEP compared to the Business Case and Road-

Map. It is recommended to immediately consider installing a second sensor in order to enable a check of the site measurements.

21 http://www.nrel.gov/docs/fy12osti/51664.pdf


56

2) Similarly to the wind resource calculations, the length of the site solar dataset is short. As a result it is recommended to perform the calculations again later in 2015, when a full year of site data is available so that all seasons will have been covered.


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9. HREP System Modelling 9.1 Introduction

It is understood that values used in the Business Case (BC) for diesel fuel use and renewable energy contribution were calculated by ABB using the Homer software package. The same Homer software, version 3.1.3, was used to estimate the renewable energy contribution for the two options and the diesel fuel consumption for the two options considered in the BC.

The Homer software can carry out its simulations in a number of ways. For the purposes of this work, the minimisation of diesel fuel consumption was selected to be the main driver. It is recommended in the future that some optimisation studies are carried out as part of the tender process to balance CAPEX, OPEX, Sustaining CAPEX and potential site constraints that may arise as part of the approvals process. It is likely that the optimisation would end up recommending some changes to the sizes of some of the main components.

The degradation of generation performance of the components over the life has not been modelled. If degradation is applied then it will have a small effect on the WTGs annual output over the life and a more significant impact on PV annual generation over the life. As a result, the analysis represents the likely performance in the first few years of operation once the operational control has been optimised.

It is recommended that further detailed optimisation analysis is carried out at tender stage which should include consideration of the entire life cycle including disposal.

9.2 Modelling Specifics

A model of each of the two BC options was built in Homer which included the following elements as applicable:

2 x 275kW Vergnet WTGs

1 x 400kW/400kWhAC Li-Ion battery and convertor

450kWpAC LHIB Solar PV installation complete with inverter

550kWpAC LHIB Solar PV installation complete with inverter

120kWpAC Private Solar PV – this is to represent the various smaller systems installed or approved to be installed throughout the grid

3 x 300kW Detroit Series 60 14l Diesel Genset

Annual Load, wind, solar radiation and temperature profiles

No attempt was made to model the current or proposed ripple control system as there was insufficient data on its actual kWh profile and the annual load data used already includes its effect. Thus introducing a deferrable load would require the contribution to be removed from the existing load data which was not possible given the lack of data. It is considered that this will only have a minor effect on the accuracy of the values calculated.

In addition, the losses from the WTG, solar and battery transformers and the 415V and 6.6kV cable losses were not include in the model. These were considered to be second order and would not impact the outcomes.

9.2.1 275kW Vergnet WTG

The Homer software includes a standard 275kW Vergnet WTG so minimal customisation was required. The power curve was confirmed as the same as was used in Section 7.3.2, and the same estimated losses were used as used in Section 7.3.4. Homer’s estimated annual unconstrained WTG kWh production was then checked against the value calculated in Section 7.3.4. Whilst the values were not identical they were within 2% which was more than sufficient for the purposes.


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9.2.2 400kW/400kWh Battery

No specific battery type has been proposed in the in previous studies for this project, although it is understood from discussions with ABB that they had modelled a generic Li-Ion battery. As a result, a generic Li-Ion battery from the Homer database was selected and the convertor was sized so that it imposes no limitation on the operation of the battery.

9.2.3 450kWpAC and 550kWpAC LHIB Solar PV

A generic flat plate solar panel was selected from the Homer library and then modified. The losses and performance characteristics, including temperature performance, were modelled as closely as possible to those carried out in Section 8 using Pvsyst. Whilst the values were not identical, they were within 6.5% which was considered acceptable for the purposes of the review.

9.2.4 120kWpAC Private Solar PV

A generic flat plate solar panel was selected from the Homer library and then modified. The losses and performance characteristics including temperature performance were based on the actual details of one of the current 4kW installations and assumed to be the same for all of the other installations. Thus a single 120kWpAC installation was modelled in Homer rather than attempting to model every individual installation. This same arrangement was modelled in Section 8 using Pvsyst and whilst the values were not identical, they were within 6.5% which was considered acceptable for the purposes of the review.

9.2.5 300kW Detroit Series 60 14l Diesel Genset

A generic 100kW diesel genest was selected from the Homer library and then modified to represent the 300kW Detroit Series 60’s that are installed. The main modifications were to upload the specific fuel curve as defined by Detroit and adjust the rating. The fuel curve was provided by Detroit Diesel [11] and is depicted in Figure 9-1 below.

Figure 9-1 : Detroit Diesel Genset Fuel Curve

The performance of the model in terms of fuel consumption was checked against the data supplied by the Board and found to be within 3% which is more than sufficient for the purposes of the review.

y = 0.2141x + 3.2744

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100

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9.2.6 Load Data

Homer has the facility to import an annual load profile. A typical annual load profile was created from the data that was received from the Board (refer to Section 5.1). The 1 minute data from the 2011 year was converted to 10 minute data and uploaded to Homer. The choice of the 2011 dataset to approximate the current state of the grid was driven by the following:

The data is the most recent and largely complete detailed data set received which approximates the current load profile. As reported in Section 5.1, the island load has reduced in recent years so this may slightly overstate the loads but much less than earlier data sets would.

This data is prior to the installation of Private Solar PV so is a true representation of the loads on the system.

9.2.7 Wind

A representative annual wind 30 minute time series dataset was created and uploaded to Homer. This time series was generated from the correlation of the site measurements and the Lord Howe Aerodrome met station data. Refer to Section 7.2 for details on this.

As noted elsewhere in this study the very limited site data does increase the uncertainty and this time series will need to be generated again when more site data is available for analysis.

9.2.8 Solar

A representative annual solar 10 minute time series data set was created and uploaded to Homer. This time series was generated from the time series created from the correlation of the site measurements and the SolarGIS data. Refer Section 8.2.4 for details on this.

As noted elsewhere in this study the very limited site data does increase the uncertainty and this time series will need to be generated again when more site data is available for analysis.

9.2.9 Ambient Temperature

A representative annual ambient temperature 30 minute time series data set was created based on the Lord Howe Aerodrome met station data and uploaded to Homer. This dataset was used predominantly for the PV output where the efficiency varies with ambient temperature significantly.

9.3 Results

The key values from the BC for each option and the equivalent calculated in this study using Homer are presented in tables with a % difference value where relevant. The BC numbers are either from the main BC document or the spreadsheet from Appendix C of the BC.

The Option 1 and Option 2 key values are shown in Table 9.1 and Table 9.2 respectively.


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Table 9.1 : Option 1 Key Values for Comparison

Option 1

550kW WTG

450kWpAC LHIB Solar

120kWpAC Private Solar

Business Case AEP

(MWh)

Jacobs AEP

(MWh)


(%)

Wind 1366.9 1393.5 2

LHIB Solar 965.8 562.8 -42

Private Solar 135.8 147.9 9

Total Solar 1101.6 710.6 -35

Total Renewable 2468.5 2104.1 -15

Excess Renewable Energy 707.7 612.8 -13

Diesel Genset 1 - 840.8 -


Total Diesel Genset Production - 934.2 -

Total Load (2011) Jacobs Homer Model 1906.5* 2345.0 -




Note:

- Includes a 400kW/400kWhAC battery

* The BC spreadsheet noted that the total load was for the period 01 April 2013 to 01 April 2014. However the data supplied by the Board showed the total load for 01 April 2013 to 01 April 2014 to be 2097MWh.

The expected monthly production from each generation source based on Option 1 and the 2011 load profile is provided in Figure 9-2 below.


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Figure 9-2 : Option 1 Monthly Energy Production

Table 9.2 : Option 2 Key Values for Comparison

Option 2

550kWpAC LHIB Solar


Business Case AEP

(MWh)

Jacobs AEP

(MWh)


(%)

Wind 0.0 0.0 -

LHIB Solar 1180.4 687.8 -42

Private Solar 135.8 147.9 9

Total Solar 1316.2 835.7 -37

Total Renewable 1316.2 835.7 -37

Excess Renewable Energy 118.0 104.4 -12



Total Diesel Genset Production - 1729.7 -

Total Load (2011) Jacobs Homer Model 1906.5* 2345.0 -




Note:


* The BC spreadsheet noted that the total load was for the period 01 April 2013 to 01 April 2014. However the data supplied by the Board showed the total load for 01 April 2013 to 01 April 2014 to be 2097MWh.


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9.3.1 Wind Annual Generation

Table 9.1 above shows agreement between the BC and the numbers calculated in this study using Homer for the AEP from the WTGs. As mentioned previously, the Homer calculated number also compares well with the values calculated using WasP in Section 7.

This provides a high degree of confidence in this number, although the short site data set and potential for high wind shear and turbulence issues which are not easily modelled may reduce the AEP in reality.

9.3.2 LHIB Solar PV Annual Generation

The LHIB Solar annual generation calculated in this study is significantly less than the figure used in the BC for either Option 1 or Option 2. The reason for this is the BC LHIB Solar generation figures are based on the NASA insolation data which has been shown to be more optimistic than the more recent and more detailed SolarGIS data (refer to Section 8.2.3) and vastly more optimistic when the site synthesised data is taken into account (refer to Section 8.2.4).

Whilst the site data is still very limited, it is the view that this lower site synthesised data is much closer to the real values than those used to calculate the BC numbers. This is also supported to some degree by the data that was able to be analysed for the existing Private Solar (refer to Section 8.3), although this was not absolutely conclusive.

As mentioned previously, the site data record is very short and this correlation needs to be repeated once there is a longer data set.

9.3.3 Private Solar PV Annual Generation

The Private Solar annual generation values are relatively similar to the BC in contrast to the LHIB Solar numbers. These values were calculated using the site synthesised solar insolation data, however it is not known how the BC values were derived.

0

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250

300

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(MW

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Diesel Genset 1 Diesel Genset 2 LHIB Solar Private Solar


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9.3.4 Diesel Fuel Consumption

The diesel fuel consumption values derived in this study for Option 1 are 20% greater than those presented in the BC which will impact the financial and economic models negatively. Curiously the difference in diesel fuel consumption for Option 2 is negligible. As the BC does not include details of how the calculations were undertaken, and efforts have been made to understand these, it is not clear why this difference occurs, possibilities could be due to the parameters used in Homer to schedule gensets and/or the fuel curve that was used.

The monthly fuel consumption values have been plotted in Section 9.5 for each of the scenarios considered.

9.3.5 Renewable Penetration

For both options much lower Renewable Penetration values were calculated than those quoted in the BC. Renewable Penetration is typically calculated as follows.

Renewable Penetration = 1Diesel Generation

Total Load

Or

Renewable Penetration =Total Reneable Generation Excess Renewable Generation

Total Load

The two reasons for the much lower Renewable Penetration values than those in the BC were determined, these are:

Significantly lower solar PV annual yields for the LHIB Solar PV which affects the numerator

Relatively higher Total Load which affects the denominator

With regards to Total Load, the value used in the BC is 1906.5MWh; this does not match the value derived from the data supplied by the Board for the same period which equalled 2097MWh. The BC spreadsheet does not include the Private Solar in the Renewable Penetration calculation, which makes sense as the load is metered after the contribution by the Private Solar for the data set they are using. This was not the case for the Homer model used in this study as mentioned above.

9.4 Further Option for Consideration

It is clear from this analysis that the contribution by the WTGs to reducing fuel and % Renewable Penetration is much more significant than the LHIB Solar PV, kW for kW.

To illustrate this a further model was run, “Option 3”, which replaces the 550kWpAC LHIB Solar PV with only the 550kW of WTGs, but still assumes the 120kWpAC of Private Solar PV. The results are shown in Table 9.3 below.


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Table 9.3 : Option 3 Key Values

Option 3

550kW WTG


Jacobs AEP

(MWh)

Wind 1393.5

LHIB Solar 0.0

Private Solar 147.9

Total Solar 147.9

Total Renewable 1541.4

Excess Renewable Energy 332.0

Diesel Genset 1 1105.8

Diesel Genset 2 124.9

Total Diesel Genset Production 1230.7

Total Load (2011) Jacobs Homer Model 2345.0

Diesel Fuel Consumption (litres) 275,826

Reduction in Fuel Consumption (%) 52.9

Renewable Penetration (%) 47.5

Note:


It can be seen from the results above that the Renewable Penetration is nearly double that of Option 2 and uses approximately 28% less diesel fuel, resulting in an overall 52.9% diesel fuel consumption saving from the business as usual case with only private solar PV installed. This also illustrates as suggested previously the need to carry out further optimisation work once more detailed site data is obtained and accurate CAPEX and OPEX numbers are known.



65


9.5 Fuel Consumption

The monthly and annual diesel fuel consumption was assessed based on the scenario where no renewables were connected to the system (from the 2011 monthly data provided by the Board) and the options described earlier in this section. Figure 9-5 shows the monthly energy fuel consumption based on these scenarios.

Figure 9-5 : Monthly Fuel Consumption

0

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250

300

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Pro

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(MW

h)

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Diesel Genset 1 Diesel Genset 2 Wind Private Solar


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The graph above shows that Option 1 provides the largest reduction in fuel consumption over the year as expected and is close to the 70% noted in the BC. The annual fuel consumption values are provided in Table 9.4 below.

Table 9.4 : Annual Fuel Consumption

Scenario Annual Fuel Consumption

(litres)

Reduction in Fuel Consumption

(%)

No Renewables 585,350 -

Option 1 209,487 64

Option 2 384,783 34

Option 3 275,826 53

Option 2 offers a reduction of just over one third of the no renewables scenario but as mentioned above is far less effective than the WTG only option, Option 3.

9.6 Diesel Genset Run Hours

The run hours for the diesel generators are provided in Table 9.5. This shows the number of hours each generator at the powerhouse was producing power based on the Homer system modelling for each option. This data will need to be used in any future modelling given diesel genset O&M costs are typically driven by run hours.

Table 9.5 : Diesel Genset Annual Run Hours

Scenario Genset 1 Run Hours

(hours)

Genset 2 Run Hours

(hours)

No Renewables 8760 5049

Option 1 3681 376

Option 2 6096 1046

Option 3 4797 508

As expected, the scenario with the lowest number of run hours is Option 1.

9.7 Diesel Genset Daily Operation

The daily operation of the diesel gensets was also briefly investigated in terms of whether they were generating or not. For this, the 21 June and 21 December data was assessed in order to capture the seasonal variation between the shortest day and the longest day, and hence the typical impact of PV contribution. The diurnal plots are displayed in the following Figures for each option. For these graphs the wind speeds on these days was quite low with an average of 4.8m/s for 21 June and 4.9m/s for 21 December which means very little energy generated from the wind.


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Figure 9-6 : Option 1 Diesel Genset Diurnal Variation

The graphs above show that during the day, after about 11:00 in winter and 10:00 in summer, the solar PV generation plus a small amount of wind generation provides sufficient generation to enable the gensets to be switched off. With the evening peak and loss of PV generation, the gensets come back on around 18:00 hours. The Homer model is structured so that the engines run in the upper end of the their efficeny curve so when the second engine is starting to help with the peak demand, it is also used to charge the battery. Although the power demand is low overnight, at least one of the gensets spends most of its time generating which is as a result of the very low wind speed. As mentioned above, both of these days selected for investigation are low wind speed days so the energy contribution from the wind turbines is amost nothing.


Similarly to the Figure 9-6, the graphs above show the gensets not generating during most of the daylight hours when the solar PV will be in operation.


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Option 3 considered none of the LHIB Solar connected to the system and as such the difference from the earlier diurnal graphs and the graphs shown in Figure 9-8 above is clear. During the daylight hours the gensets are generating on these selected days, where previously there was a large contribution from the solar PV during this time and the gensets were offline. These selected days are low wind speed days hence Option 3, where the WTGs are the only renewable energy source apart from the Private Solar, requires the diesel gensets operating more frequently. This is not expected to be norm based on the island’s wind resource.

The following additional graphs have been prepared to illustrate the proportionally greater contribution to generation of the wind than the solar.

Figure 9-9 : Option 1 Diesel Genset Diurnal Variation – Average Daily Wind Speed of 7.1m/s


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And for comparison purposes, the following graphs show a day when the average wind speed is 13.7m/s so the wind turbines would be producing maximum power output.

Figure 9-12 : Option 1 (left) and Option 2 (right) Diesel Genset Diurnal Variation – Average Daily Wind Speed of 13.7m/s


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10. Potential Equipment Suppliers A brief review was undertaken of the various suppliers in the market who could provide the main items of plant equipment to assess whether there is likely to be any issues with the supply of equipment. It was clear that this project has attracted a lot of interest and there is a strong desire of suppliers and engineering organisations to be involved. As a consequence, obtaining some competitive tension in a tender process is not expected to be an issue.

10.1 Wind Turbines

Whilst the project has so far been developed using a Vergnet 275kW WTG, a brief investigation of other possible wind turbine suppliers suitable for remote island applications was done. Table 10.1 displays the suppliers and models that were considered.

Table 10.1 : Wind Turbine Supplier Options

Supplier Model Capacity

(kW)

Survival Wind Speed

(m/s) Tower Type

ACSA A27/225 225.0 - Tubular or lattice

Atlantic Orient Canada AOC 15/50 50.0 59.5 Tubular or lattice

Enercon

(no longer produced by Enercon) E33/330 330.0 - Tubular

Energie PGE PGE 20/50 50.0 52.0 Tubular or lattice, tilt up version

available

Energie PGE PGE 20/35 35.0 52.0 Tubular or lattice, tilt up version

available

Fuhrlander FL 250 250.0 67.0 Tubular

Fuhrlander FL 100 100.0 67.0 Tubular

Fuhrlander FL 30 30.0 55.0 Lattice

Proven Proven 15 15.0 70.0 Steel tower

Turbowinds T400-34 400.0 60.0 Welded steel cylindrical tapered

Turbowinds T300-28 300.0 62.0 Welded Steel soft tower

Vergnet GEVMP 275 275.0 83.0 Steel tilt down tower

Windflow Windflow 500 500.0 - Tubular

WTIC Jacob 31-20 20.0 53.6 Lattice

WTIC Jacob 26-17.5 17.5 53.6 Lattice

WTIC Jacob 26-15 15.0 53.6 Lattice

WTIC Jacob 23-12.5 12.5 53.6 Lattice

There are a significant number of wind turbines in the market as evidenced by the list above and many of these have been used in remote locations, but there are very few that match the specific desirable characteristics of the Vergnet WTG. The use of a WTG other than the Vergnet WTG is possible and any tender process would require the tenderer to address the specific LHI issues which have so far driven the selection of the Vergnet WTG.

10.2 Batteries There are a number of battery manufacturers and engineering firms that have alignments with battery manufacturers covering a range of battery technologies that are currently active in the Australian market. It is


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not considered that there will be any issue in gaining traction with tenderers in relation to the supply of batteries for this project, despite some of the logistical issues associated with delivering a large battery to site.

Companies such as ABB and Siemens have already both expressed a desire to undertake this project and both can point to similar projects that they have undertaken elsewhere in the world recently, typically with Li-Ion batteries. Other businesses, such as Ecoult who offer energy storage solutions using a hybrid lead acid battery, have also expressed a desire to provide the energy storage solution for this project.

10.3 Solar Panels

There is a large variety of PV panel and inverters on the market that would be suitable to be installed at Lord Howe Island.

Table 10.2 provides manufacturer details from PV projects above 150kW that have been constructed in Australia in the last 5 years. The table covers installations in a large variety of environments including installations undertaken on rooftops.

Contractor and panel manufacturer information was readily available, but the inverter manufacturer was not listed in all cases.

Table 10.2 : Australian Solar Project Equipment Manufacturers

Project State Capacity

(kW) Main Contractor Panel Inverter Status

Nyngan NSW 102000 First Solar First Solar Central SMA Under construction

Broken Hill NSW 53000 First Solar First Solar Central SMA Under construction

Royalla ACT 20000 Acciona Jinko N/A Operational

Greenough River WA 10000 First Solar First Solar Central SMA Operational

University of Queensland (St Lucia campus)

QLD 1220 Ingenero Trina Solar N/A Operational

NextDC M1 Data Centre VIC 400 Energy Matters REC N/A Operational

Fraser Coast QLD 400 Ingenero Suntech N/A Operational

Toyota Altona North VIC 500 Autonomous Energy Kyocera ABB Operational

Solar Farm Carnarvon WA 290 EMC / Carnarvon Electrics SunPower Fronius Central Operational

Queensland University of Technology

QLD 202 Ingenero SunPower N/A Operational

Johnson & Johnson NSW 200 Apolo Energy Sanyo HIT SMA Operational

Araluen Arts Centre NT 162 Ingenero Q.CELLS SMA Operational

The table above shows a variety of contractors, panel manufacturers and inverters, although it is clear that SMA has a strong position. In addition, Jacobs has been involved with obtaining quotes for PV projects for islands in the Pacific from suppliers such as Solartech and RFI, proposing panel manufacturers such as CEEG, Suntech and Bosch connected to SMA and Samil inverters.

10.4 Control System

It is considered that the control system, which successfully controls the HREP and seamlessly operates this in the LHI grid whilst minimising the diesel fuel usage and run hours of the diesel gensets, will be the most challenging engineering task of this project. There are a number of examples within Australia and internationally where systems have been successfully implemented and run for considerable periods of time demonstrating that it can be done.


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The BC for the LHI HREP sets very high renewable energy penetrations22, and significant diesel fuel consumption reduction targets. To achieve the fuel reductions in the order of what is proposed will require the efforts of a control system provider with significant proven track record to ensure that there is no loss of continuity of supply whilst commissioning and tunning the system and meeting these targets.

ABB (formerly Powercorp) has significant experience and a proven track record in this space within Australia, but are not the only possibility. It is considered that a tender process for supply of the control system of the project will elicit a number of responses from different providers and will hence maintain competitive tension in the process.

As a final comment in relation to the control system, it is known that work is being carried out by some providers to include predictive elements to the control system, such as sky measurements to assess cloud movement and the impact on output from the solar systems. Whilst not necessarily a requirement for the HREP as currently proposed, predictive control strategies offer the opportunity to minimise the use of diesel gensets further and hence increase the fuel savings. As such this should be part of the assessment of any service provider.

22 As shown in Section 9.3.5 it is considered that the % penetrations as proposed in the BC case are unachievable with the system proposed,

however the % penetrations calculated in this study are still considered to be high.


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11. CAPEX and OPEX 11.1 Capital Cost Estimate Review

The breakdown of CAPEX in the BC for Option 1 and Option 2 is shown in Table 11-1 and Table 11-2 below. The breakdown is done at a very high level and is linked to the ARENA agreement milestones. As the data presented in the business case was very course it was not easy to make specific comparisons of wind solar battery and control system costs.

Table 11-1 Option 1 - Capex Summary from the AECOM Business Case

Table 11-2 Option 1 - Capex Summary from the AECOM Business Case

The costs of the wind, solar and battery systems were briefly examined to assess whether the overall budget estimate was likely to be adequate. Whilst the HREP is not unique there are not numerous similar installations that would enable simple cost metrics to be applied as is typically applied for large scale wind or solar development.

A number of suppliers were approached for budget estimates for design, supply, installation and commissioning costs. Transport was to Port Macquarie only, the cost of transport to LHI and on LHI was considered too difficult to address at this stage by the suppliers. As a general statement the suppliers whilst keen to be involved and to assist where they can due to the interest in the project were also reluctant to provide costing information ahead of an official tender.

The results of the inquires lead to the following Table 11-3 of costs for Option 1 and Option 2. A 15% contingency was recommended based on the number of unknowns at this stage. The table does not include the cost of freighting from Port Macquarie to the site as the suppliers generally were unable to give details of the volumes equipment that are expected to be shipped.

Category Total Year 1 Year 2 Year 3 Year 4 Year 5Provide Updated Project Plan, Concept Design Milestone 1 $ 280,000 Commence Avifuana & Meteo Data Collection Milestone 2 $ 220,000 Technical Feasibility and Design Review Milestone 3 $ 147,000 Treasury Funding Approved Milestone 4 $ 300,000 Tender completion and investment decision Milestone 5 $ 550,000 Solar PV permitting and precurement Milestone 6 $ 2,505,000 Solar PV commissioning Milestone 7 $ 1,570,000 Wind Permitting and Precurement Milestone 8 $ 3,660,000 Practical Completion and procurement Milestone 9 $ 500,000 Delivery of Financial Report Milestone 10 $ - 12 Months of Operation and Final Report Milestone 11 $ 100,000

Sub-Total $ 947,000 $ 3,055,000 $ 5,230,000 $ 500,000 $ 100,000 Contingency $125,594 $233,099 $358,614 $45,743 $4,950

Total CAPEX incl. Contingency 10,600,000$ $ 1,072,594 $ 3,288,099 $ 5,588,614 $ 545,743 $ 104,950

Category Total Year 1 Year 2 Year 3 Year 4 Year 5Provide Updated Project Plan, Concept Design Milestone 1 $ 280,000 Commence Avifuana & Meteo Data Collection Milestone 2 $ 220,000 Technical Feasibility and Design Review Milestone 3 $ 147,000 Treasury Funding Approved Milestone 4 $ 300,000 Tender completion and investment decision Milestone 5 $ 550,000 Solar PV permitting and precurement Milestone 6 $ 2,505,000 Solar PV commissioning Milestone 7 $ 1,570,000 Wind Permitting and Precurement Milestone 8 $ - Practical Completion and procurement Milestone 9 $ 500,000 Delivery of Financial Report Milestone 10 $ - 12 Months of Operation and Final Report Milestone 11 $ 100,000

Sub-Total $ 947,000 $ 3,055,000 $ 1,570,000 $ 500,000 $ 100,000 Contingency $125,594 $233,099 $156,436 $45,743 $4,950

Total CAPEX incl. Contingency 6,737,822$ $ 1,072,594 $ 3,288,099 $ 1,726,436 $ 545,743 $ 104,950


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Table 11-3 Option 1 and 2 Major Items of Plant Capex

Option 1 Option 2

Wind Turbines $ 2,442,903 $ -

Batteries 400kW/400kWh $ 1,150,000 $ 1,150,000

Control System $ 750,000 $ 750,000

Solar Panels 450kW $ 2,211,898 $ 2,703,431

15% Contingency $ 983,220 $ 690,515

Total $ 7,538,021 $ 5,293,946

The following points in relation to these costs are made;

- The wind turbine costs are in the order of what is expected.

- The costs provided by the suppliers approached for the batteries are likely to be at the upper end and with the current trend of battery costs reducing and a competitive tender process it is expected that the battery costs will reduce.

- The Solar panel values are considered to be at the upper end as well and will likely reduce with a competitive tender process. The suggested installation costs by contractors were very high and it is believed that once the site is understood by contractors that there will be more cost effective installation solutions.

The values shown for Option 1 are approximately $3m less than the total BC number. This amount is therefore available to undertake the items not covered in Table 11-3, such as the environmental approvals, Owners Engineer and Community Consultation and is expected to be an adequate allocation

The values shown for Option 2 are approximately $1.5m less than the total BC number. This amount is considered adequate to undertake the items not covered in Table 11-3, such as the environmental approvals (which should be much lower than the Option 1 cost given the lower threshold approvals and subsequent investigation and documentation), Owners Engineer and Community Consultation.

Regardless of which option is selected it is recommended that a detailed budget is prepared as part of the next stage of work so that detailed information is available for the investment decision milestone.

11.2 Operational Cost Estimate Review

The BC case OPEX figures are based on ABB’s [5] previous work. The numbers are based on the assumption that the cost of WTG, solar and battery systems maintenance is largely offset by the reduced diesel genset maintenance. This assumption is considered reasonable. Once the systems are commissioned and the initial tuning issues are rectified it is expected the system will require minimal maintenance activities. It is expected that once the existing Powerhouse Operator and the apprentice electrician are trained that they will be able to carry out all necessary servicing activities

The WTG’s will require annual servicing but this is no more onerous than a major service on the diesel gensets. The solar PV and battery systems will only require regular checks and occasional breakdown maintenance requiring replacement of parts. The solar panel area will also require some treatment of the grass/weeds around and under the solar panels.

There is an allowance in year 11 of operation for Sustaining Capital or replacement of major components at the end of their life. This is driven by the replacement of battery cells which have 10 year typical life. The number allowed for here appears reasonable but should be reviewed once the size and type of battery system is settled on and firm pricing is obtained.


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12. Schedule Review The BC program has the project complete at the end of December 2017. This overall timing and allocations for the major items is reasonable assuming a sufficiently long record of site data is available to issue to the tenderers and to use in the analysis for an investment decision. Unfortunately at the time of writing of this report there was only 4 months worth of data and a further 8 months would be preferential.

Due to the issues raised in this report about the wind and solar resources it is critically important that 9 to 12 months of data is available for the tender process and final investment decision. If the tender process commenced after there was 9 months worth of data available this would mean that tenders would be called in September 2015.

Following the responses from tenderers it would be possible then to optimise the project size based on firm contract numbers and detailed site data. This should be able to be completed so that an investment decision is made by the end of 2015 which would be a 3 month delay on the current program.

In summary it is recommended to vary the following ARENA Milestones;



Milestone 7 to 12 may also need to be delayed by 3 months leading to a project completion 31 March 2018. However it is recommended to delay making this change until after tender responses are received.


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13. Power System Studies Jacobs has carried out a Power Systems Study for the HREP, the following text is an extract from the report for this study [12].

The purpose of the Power System studies is to confirm that the proposed wind, solar and battery system integration to the Lord Howe Island electricity grid provides a stable network, capable of supplying power with levels of quality and reliability compliant with Australian Standards and LHI users’ expectations.

Power on the island is currently provided by 3 x 300kW diesel generators supplying peak loads from 400kW to 470kW and average loads ranging from 250kW to 280kW depending on the season. The Board also has one 424kW backup generator for emergency situations which was not included in any of the studies as it is never synchronised with the main 3 x 300kW generators. The island currently has load management of the solar water heater boosters.

The Board provided the monthly maximum demand (in Amps) for each substation over the past five years (2010 to 2014). The assessment of the historical load on LHI shows a very minimal or no load growth over the last five years. Therefore, the assessment has been based on 2014 LHI loading levels assuming no growth from 2014 to 2018. The total load at each substation was set to the maximum substation demand across 2014 based on information supplied by the Board. A diversity factor was then applied to scale network loads to equal the total diversified LHI load. The total diversified load has been based on the loading levels provided by the Board for 2014 as following:

Minimum demand (overnight time with no private rooftop solar): 148kW

Minimum demand (daytime with full private rooftop solar): 170kW

Maximum demand: 428kW

This assessment has been based on the power system proposed in the AECOM 2014 Business Case [2] and with reference to the earlier documents, Lord Howe Island Renewable Operations Energy Supply Road-Map [3] and the Roadmap Implementation Technical Design Specifications [4]. Option 1 of the proposed HREP includes 450kWpAC of centralised solar PV and 550kW (2 x 275kW) of wind generation. Option 2 of the HREP replaces the WTGs with an additional 100kWpAC of solar PV installation increasing the centralised solar PV to 550kWpAC. This generation is supported by a 400kWAC/400kWhAC Battery Energy Storage System (BESS) combined with a demand management system to ensure stable operation despite the high level of renewable penetration. The modelling was carried out including the existing installed private and approved but not installed solar installations totalling 120kWpAC.

In order to undertake the power system studies, a model has been developed of the LHI power network in DIgSILENT software. This model represents the existing LHI network and proposed systems. As the Business Case defined the choice of WTG as the Vergnet 275kW machine the DIgSILENT WTG model was developed using specific information provided by Vergnet and as such should closely replicate the real world performance of the WTG as opposed to using a generic model. The solar and battery energy storage system (BESS) models were developed using information and models from ABB. Whilst ABB has not been selected to supply this equipment, their past history with this project and stated intention to bid in the future has meant they were both well informed on the project requirements and willing to provide the DIgSILENT model information. The same information could potentially have been obtained from other suppliers but would likely have been a much slower process whilst they came up to speed with the project.

Power system studies were undertaken for both steady state and dynamic stability conditions.

13.1 Steady State Studies

The LHI network steady state operation has been assessed under various network load and Private Solar roof top output scenarios, refer Table 13.1, mainly to assess the impact on the network voltage and network thermal loading.


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Table 13.1 : Steady State Studies Scenarios

Scenario No. Operating Conditions LHI Load23

(kW) Private Solar Status

Scenario 1 2018 daily light load during night – assuming no solar generation 148 No solar

Scenario 2 2018 daily light load during daytime – assuming maximum private rooftop solar generation

287 Maximum solar

Scenario 3 2018 daily peak load – assuming no solar generation 545 No solar

Scenario 4 2018 daily peak load - assuming maximum private rooftop solar generation 545 Maximum solar

The following conclusions have been made from the study results.

1) Network steady state voltages remain between 0.96 – 1.01p.u and are satisfactory.

2) The network voltage unbalance varies by only 2% across all three phases across the network and is satisfactory.

3) The network observes the lowest voltages when the private roof top solar PV is not in operation under a high load conditions as the entire load will be supplied from the powerhouse (i.e. mixture of all the energy plants except the Private Solar PV).

4) The voltage variation across the daily load cycle (including variation with roof-top solar) is around 1%. This is a satisfactory result.

5) The network thermal loading across the network remains within the equipment thermal ratings for all the scenarios.

6) Thermal loading will be the highest under a high load conditions with no roof top Private Solar PV generation.

13.2 Dynamic Studies

The dynamic behaviour of all the existing and proposed generating plants and, the LHI network has been assessed for various contingencies (such as loss of load, loss of generation and network faults) under various network load and generator dispatch conditions (Table 13.2).

23 This load represents the actual network loading before being offset by the rooftop solar generation.


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Table 13.2 : Dynamic Studies Scenarios

Scenario No. Operating Conditions Contingency

1 2018 daily peak load – assuming all solar generating to the maximum capacity

Sudden loss of the central Solar PV plant

2 2018 daily peak load – assuming wind generating to the maximum capacity

Sudden loss of one wind turbine

3 2018 daily low load scenario – night, limited loads, assuming maximum wind power generation

Wind gust (step change from 11m/s to 16m/s)

4 2018 daily peak load – assuming a mix of solar, wind and Diesel in service – to assess how all different generation sources with their control systems interact

1) Sudden change in system load (loss of one feeder supplying either north or south regions zone subs)

2) Sudden loss of Diesel generator

5 2018 daily peak load – assuming one diesel generator in service 1) Fault on 6.6kV network for 200ms

2) Fault on 415V network for 50ms

6 2018 daily low load scenario – night, limited loads 1) Fault on 6.6kV network for 200ms

2) Fault on 415V network for 50ms

The following conclusions have been made from the study results:

1) The BESS will be primarily managing the network frequency and voltages as per the droop settings under all the contingency conditions assessed.

2) The diesel generators will assist in frequency and voltage control when operating as per their droop settings (which will be set higher than the BESS).

3) In order for BESS to manage the load balance either by supplying or absorbing the power into or from the network respectively, the battery system will need to be charged between 20-80% of its rated capacity. The optimal battery system capacity and charge level needs to be determined at the detailed design stage based on the optimal generator dispatch and scheduling.

4) In fast transient events such as wind gusts, the BESS needs to have enough capacity to absorb high power generation almost instantaneously. If this is not possible then the HREP will need to operate other forms of generation (i.e. Wind, Solar or Diesel) at appropriate levels along with the BESS to manage this instantaneous power increase by quickly reducing their power output levels. The appropriate level of other generation would be determined based on the optimal generator dispatch and scheduling.

5) Under various contingencies such as loss of load or generation or network faults, over or under frequency events with very large frequency deviations were observed. This situation mainly occurs when the network operates with low system inertia (i.e. no conventional generator in service or no wind turbines). This situation can lead to network instability or tripping of various plants due to over or under frequency. This situation can be alleviated by providing some additional inertia into the system by introducing some rotating machine such as diesel generators, a rotating flywheel system or wind turbines.

6) Appropriate solutions to increase the system inertia need to be evaluated considering their technical and commercial feasibility and considered in the detailed design and operational strategy.

7) Option 2 of the HREP which replaces the wind turbines with an additional 100kWpAC of solar PV, as proposed by the AECOM Business Case, may increase the risk of reducing the system inertia further and hence compounding the frequency excursion issues.

8) The dynamic models of the plants do not include the protection settings and do not trip the plant for the under and over frequency events mentioned in (5) above. It is recommended that the detailed protection settings for all of the plants are reviewed during the detailed design stage. The frequency settings need to be set to avoid any nuisance tripping of plant.

9) The network voltages due to a 3ph-Short Circuit (SC) fault on the network will drop to close to the zero volts. It is recommended that the zero Fault Ride Through (FRT) capability of all the generating plants is confirmed. It is important that all the items of plant can ride through such faults on the network.


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10) A 3ph-SC fault on the LV network during the low load condition where the entire load was supplied by the BESS resulted in the network being unstable as the required active and reactive power exceeded the BESS rating. This situation can be alleviated by:

a) Additional generation along with the BESS

b) Increasing the size of the BESS

c) Operating one of the diesel generators at low or optimal loading conditions

These solutions will need to be evaluated further technically and commercially to optimise the generation mix to avoid such conditions.

11) A detailed design for the protection coordination and assessment of the optimal generator dispatch and operating strategy needs to be undertaken as part of the process of settling on the final specifications for all the proposed plant. Further studies will be required to achieve the optimisation and coordination in the LHI network.


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14. Protection Study A Protection Study for the HREP has been carried out [13], a summary of which is provided in the text below.

The electrical protection philosophy and systems needed to integrate the new Hybrid Renewable Energy Project (HREP) power plant into the Lord Howe Island Network were analysed.

Existing protection systems in use in the network are very simple, being based on:

6.6kV over current and earth fault relays

6.6kV transformer fuses

OEM provided protection for the diesel generators

Small network embedded 415V PV plant protection that trips the PV plant when voltage/frequency is out of limits

The existing systems will continue to be fit for purpose after the HREP power plant is placed in service, except in the diesel generator powerhouse where two new 415V protection relays, (with both a reverse power protection function and a check synchronising permissive), should be added to the existing 500kVA generator transformer protections.

The two 275kW wind turbines, 450kWpAC solar PV generator, and 400kW battery that are the generation sources in the HREP power plant will each require OEM proprietary protection and automatic synchronising systems.

The HREP power plant causes:

A reduction in Lord Howe Island network 6.6kV fault levels

Bidirectional power flows via the new 6.6kV battery and solar switchboard located between the existing 6.6kV network and the various hybrid renewable generation sources

Hence some sophistication is needed for the protection systems used at the 6.6kV battery and solar switchboard. The protection that is used on each of the four 6.6kV feeders emanating from this particular switchboard needs to be an “interconnector” relay specifically designed for connecting wind farms and PV plants into distribution networks. Specific protection and check synchronising functions have been nominated that will need to be armed on each particular 6.6kV feeder “interconnector” relay.

Finally, the potentially low 6.6kV fault levels and bidirectional power flows warrant the use of a busbar protection scheme at the 6.6kV battery and solar bus switchboard to provide sensitive quick acting protection of the switchboard itself.


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15. Communications Study A Metering and Control Communication Study for the HREP has been carried out [14], a summary of which is provided in the text below.

The study explored whether adoption of a two way communications network and incorporation of end point utility services including demand management can be integrated successfully and efficiently within the Lord Howe Island environment.

The limited demand management capability via the existing ripple control system used for hot water load control has reached the end of its economic life.

The communication study analysed technologies available and commonly used, including multiple radio frequency communications systems and fixed wired communications systems.

Energy utilities are choosing to install two way communications to customer premises to enable a number of critical utility functions including:

1) Demand management (as a replacement for ripple control systems)

2) Meter reading (periodic, move in and move out)

3) Energy network customer end point monitoring and outage detection

4) Multi-tariff loads including electric vehicle charging

5) Load limiting as agreed in a customer contract

6) Managing distributed generation at the customer premises (solar, fixed or vehicle battery, wind)

This study explored whether adoption of a two way communications network and any of these end point services can be integrated successfully and efficiently within the LHI environment.

The recommended solution, with the best fit to LHI’s requirements and meeting the local environmental constraints, is a Distribution Line Carrier (DLC) with Broadband Power Line (BPL) backhaul as shown in Figure 15-1. This is an end-to-end solution using the existing underground power cables for all communications. Since it does not rely on radio frequency communications, the solution has a low visual profile and avoids the need to estimate coverage through existing vegetation.

Figure 15-1 : Details of the proposed end-to-end metering solution

Components have been identified which have been shown to work together, simplifying the task of system integration. Importantly the components are likely to have already been incorporated into the back office systems offered by that vendor, which may be of significant additional benefit to the Board.


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This communication technology which is available now, is currently being used to support several large meter deployments in international markets. The solution is currently being implemented following successfully trialling at a large Australian distribution utility.

The communications recommendations made in the ABB Technical Design Specifications [4] were reviewed as part of this study. The solution proposed in this Technical Feasibility Study differs significantly from that proposed by ABB which is not considered to address the Boards’ needs.


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16. Geotechnical Investigations A Geotechnical Investigation for the HREP has been carried out [15], a summary of which is provided in the text below.

16.1 Basis of Recommendations

A geotechnical investigation of the area proposed for WTGs and solar panels was carried out. This section provides a brief overview of the work undertaken and general recommendations for excavations and foundations. The intent of this section is to provide a geotechnical summary only, for design purposes this summary should be read in conjunction with the full Geotechnical Investigation Report including bore logs and laboratory results.

At the time of preparing the Geotechnical Investigation Report, no specific information on foundation loads, excavation depths or final surface levels was available. In addition the locations of the infrastructure and generation equipment are still being developed and could be subject to change. Thus, the information provided in this study and the full Geotechnical Investigation Report is a guide only to provide factual information and design parameters for excavation conditions, access road construction and foundation types. It may be necessary during the detailed design and construction phase to seek further geotechnical advice to confirm assumptions made.

In summary, the geotechnical investigations comprised eighteen (18) test pits excavated to depths of 0.3 to 2.3m with an excavator. Six test pits were located in lot 101, the proposed wind turbines area, and 12 test pits were located in lot 230, around the proposed solar panel array area and along the access road alignment. A select number of laboratory tests were undertaken on soil samples obtained from site for subgrade and durability property assessment.

The following provides a summary of the recommendations made in the Geotechnical Investigation Report during the test pitting programme.

16.2 Earthworks

16.2.1 Excavation Conditions

Trench excavation will be required for power distribution purposes, with trenching invert levels understood to be in the order of 1000 to 1200mm. Trench excavation is likely to occur in stiff to hard clay soils, with areas of shallow basalt outcrop expected in the higher part of the solar array area and along the ridge line at the turbine area.

Excavation will be achievable with conventional excavation equipment (i.e. excavators/backhoes) in the areas with stiff to hard clays but in the areas of basalt outcrop, the use of hydraulic rock picks/hammers, pre-drilling or blasting may be required.

16.2.2 Access Road

The access track is likely to consist of a bitumen sealed track, primarily used to enable access around the site for construction plant and future light vehicle access for maintenance and monitoring.

In the lower lying areas adjacent to the powerhouse, softened materials (unsuitable) were encountered to a depth of 0.5m. It is understood that this area is in an old drainage line which can become water logged during periods of high rainfall. Soil types with higher silt contents when saturated can be problematic to compact and more susceptible to strength loss.

Based on the above the following subgrade and unsuitable material treatments are recommended under footprints of structures, buildings and the access road:


84

All areas are to be stripped of all topsoil and organic matter (if present) which may prevent subsequent layers of engineered materials achieving the specified level of compaction.

Compact and proof roll all exposed soil surfaces with a minimum of 8 passes of a roller of at least 5 tonnes per metre width static weight capacity to detect any soft or compressible areas (or other suitable site equipment such as loaded dump truck). If any unacceptable materials or excessive heaving is found, then they should be excavated and replaced with a compacted engineered fill. Engineered fill should be placed in layers of no more than 250mm loose thickness and compacted to 98% of the standard maximum dry density (SMDD), within -2% to +2% of the optimum moisture content (OMC).

In the low lying areas, the sub-grade soils may need to be treated by over excavation of 500mm and replacement with a bridging layer of material comprising crushed rock wrapped in geotextile to assist in all-weather access and trafficability. It is understood that there is the opportunity for the use of a recycled glass product from the island, which can be crushed to form a product with a size range of 3 to 8mm. Provided the geotextile is specified with a higher grade (i.e. Bidum A64) to reduce potential for tear and puncture, the use of these materials should be feasible subject to assessment on site to determine appropriate layer thicknesses.

Provided the subgrade preparation and treatments recommended above are undertaken, and adequate road cross fall and drainage is provided to prevent subgrade saturation, a design subgrade CBR of 3.5% can be adopted for pavement design.

16.2.3 Wind Turbines

The wind turbines are proposed to be located along the ridge line where shallow bedrock is expected. Foundations options include pad footings and mass concrete supports or anchor bars for cable stays.

For high level pad footings, it is recommended that foundations are extended onto the top of bedrock and designed for an allowable vertical bearing pressure of 1000kPa. For lateral capacity calculations of mass concrete supports and footings, the following soil parameters in Table 16.1 can be adopted for clay soils, (stiff or better) to estimate lateral capacity (assuming level ground, less than 15% grade/cross fall).

Table 16.1 : Anchor Footings

Unit No. Unit name Soil Bulk Density24

(kN/m3)

C’ (Drained)

(kPa)

Phi (Drained)

(degrees)

Cu (Undrained)

(kPa)

Modulus

(Mpa)

Unit 3 Residual soil 12 5 30 75 20

For guy rope supports attached to grouted dowels/bars into bedrock, an ultimate bond adhesion of 500kPa could be adopted. Higher capacities and bond adhesions may be feasible, but subject to proof testing or further investigation at the time of installation.

16.2.4 Solar Panel Arrays

For the design of solar panel array pole supports, it is expected that shallow rock is likely at the current solar panel site. As such, supports will likely need to be socketed into hard rock to provide lateral support by drilling/coring methods. In other areas, where deeper soil is expected > 1.0m, there is considered a risk of lateral slope creep movement of the upper clay soils in steeper areas. Solar array foundations may need to be socketed a minimum of 500mm into bedrock and designed for an allowable lateral and vertical bearing capacity in bedrock of 500kPa. Lateral support of the upper soils should be ignored for calculation purposes.

24 A lower bulk density for the clay soils had been adopted based on results of testing.


85

16.3 Further Assessment

Based on the results of the geotechnical investigations, the key issues and risks identified that need to be considered or further assessed include:

For wind turbine foundations, foundation loads are not expected to be high, with lower bound ultimate bond stresses adopted based on level of testing undertaken (test pits only). If higher capacities are warranted, borehole drilling and coring or proof testing at time of installation could be undertaken.

Creep movement on clay slopes for solar panel array post footings. It is currently recommended that all posts and footings be socketed into underlying rock. If shorter posts in clay soils are being considered for constructability purposes, further geotechnical advice should be sought.

As discussed above, depending on the alignment of trenches and depth of footings, rock excavation in hard rock is likely. Allowances should be made for rock breaking and potentially blasting to achieve levels for excavation and methods for drilling posts to achieve required embedment.

Once site locations and structure details have been determined, further geotechnical input may need to be sought to confirm assumptions and recommendations made above.


86

17. Recommendations A number of recommendations have been raised throughout this study. A summary of the recommendations resulting from this study are provided below:

Table 17.1 : Recommendations

Number Recommendation Responsible Party Date for Completion

1 The wind turbine suitability for site will need to be confirmed by the wind turbine supplier

WTG supplier November 2015

2 The calculated wind shear at the site monitoring mast is high and this should be monitored and re-assessed as more data is recorded by the site monitoring mast


3

The length of the site wind data available is short and has increased uncertainty associated with the calculations. The long term wind speed and AEP should be recalculated later in 2015, once a full year of site data is available.


4

The synthesised solar site data determined in this study results in a much lower AEP compared to the Business Case and Road-Map. It is recommended to immediately consider installing a second sensor in order to enable a check of the site measurement.

LHI Board April 2015

5

Similarly to the wind resource calculations, the length of the site solar dataset is short. As a result it is recommended to perform the calculations again later in 2015, when a full year of site data is available so that all seasons will have been covered.


6

The maximum demand of the electrical system is critical for determining the amount of “spinning” reserve required to ensure system stability. There is a discrepancy in relation to the magnitude of the measured peak load at LHI from different data sources. This will need to be investigated further and the actual peak vales determined.


7

It is recommended in the future that some optimisation studies are carried out as part of the tender process to balance CAPEX, OPEX, Sustaining CAPEX and potential site constraints that may arise as part of the approvals process.

Jacobs and Tenderers

Tender stages

8 Update the wind and solar input time series datasets used for the Homer modelling when more site data is available for analysis and re-run the Homer models based on the updated datasets.


9 It is recommended that further detailed optimisation analysis is carried out at tender stage and that this analysis includes consideration of the entire life cycle, including disposal.

Jacobs and LHIB Tender stages

10 A requirement of the control system tender should include optionality for predictive control strategies which enable the opportunity to run the HREP system more efficiently.

Control System Tenderer

Tender stages

11

The following ARENA Milestone dates are varied



LHIB July 2015


87

18. Conclusions This study on the proposed HREP concluded that both Option 1 and Option 2 of the HREP are technically feasible. However there are number of aspects that require further investigation to remove unknowns or reduce uncertainty. The study makes a number of recommendations to address these issues, a list of the recommendations is provided in Section 17 of this study.

The most important recommendation is a further review of site wind and solar data once more data, preferably 9 months more is obtained. This is necessary so:

The WTG supplier can confirm the suitability of the equipment for the site, given the site data to date has indicated the potential for high wind shear

To optimise the size of the equipment

The key results of the system modelling of the two proposed HREP systems are provided in the table below, along with the results from the Business Case for comparison.

Table 18.1 : HREP System Modelling Key Results

Scenario AECOM

Business Case

Jacobs

Technical Feasibility


(%)

Option 1




Option 2




It can be seen from the table above that this study predicts a lower reduction in fuel consumption than the Business Case and also a lower Renewable Penetration percentage. Based on the analysis in this study, the difference in Renewable Penetration and fuel consumption is due to a higher estimate of the 450kWpAC and 550kWpAC LHIB Solar PV contributions in the earlier studies. The higher estimate is understandable as there was no site data at the time of those calculations and the current site data is indicating lower solar energy than was assumed previously.

It is clear from the above that Option 1 offers a significantly larger reduction in fuel consumption than Option 2.

A third option of the HREP system was modelled. This system was similar to Option 1 with the exception that the 450kWpAC LHIB Solar PV was removed. This modelling highlighted the significance of the wind contribution to the total renewable generation when compared to the solar PV only case (Option 2). The third option achieved a 47.5% Renewable Penetration and a 53% reduction in fuel consumption, demonstrating that the wind generation component provides by far the greatest contribution to fuel savings.

This however does not mean that solar PV should not be installed. Further analysis of the component sizes, including the battery system size, is recommended at the time of tendering to optimise the system technically and from a life cycle cost perspective.

A brief review was undertaken of the various suppliers in the market who could provide the main items of plant equipment to assess whether there is likely to be any issues with the supply of equipment. It was clear that this project has attracted a lot of interest and there is a strong desire of suppliers and engineering organisations to


88

be involved. As a consequence, obtaining some competitive tension in a tender process is not expected to be an issue.

A review of costings showed that the BC allocations were most likely sufficient; however, until the tender process is completed, and firm costings are obtained this will not be certain. The final project completion date (system is fully operational) is likely to be delayed by 3 months principally due to the additional time needed to obtain a longer site data record.


89

19. Bibliography

[1] Land and Property Information, “Lord Howe Island Satellite Imagery,” 2011.

[2] AECOM, “Lord Howe Island Hybrid Renewable Energy Project, Business Case,” 2014.

[3] Powercorp, “Lord Howe Island Renwable Operations Energy Supply Road-Map,” 2011.

[4] ABB, “Lord Howe Island Energy, Roadmap Implementation, Technical Design Specifications,” 2013.

[5] ABB, “Stage2: Plan B Business Cases,” 2012.

[6] Australian Bureau of Meteorology, “Lord Howe Island Aero met station data,” 2015.

[7] International Electrotechnical Commission, “IEC 61400-12-1 Ed. 1 Wind Turbines: Power performance measurements of electricity producing wind turbines,” 2005.

[8] International Electrotechnical Commission, “IEC 61400-1 Ed. 3 Wind turbines: Design requirements,” 2005.

[9] Vergnet, “GEVMP 32/275L Power Curve,” 2009.

[10] Vergnet, “GEVMP 32 Thrust Coefficient Curve,” 2012.

[11] Detroit Diesel, Genst Series 60 Performance Specification, 2007.

[12] Jacobs, “Hybrid Renewable Energy Project, Power Systems Study,” 2015.

[13] Jacobs, “Hybrid Renewable Energy Project, Protection Study,” 2015.

[14] Jacobs, “Hybrid Renewable Energy Project, Metering and Control Communications Study,” 2015.

[15] Jacobs, “LHIB Hybrid Renewable Energy Project, Geotechnical Investigation Report,” 2015.

[17] Vergnet, “GEVMP-C Civil Works description,” 2010.

[18] Vergnet, “TUB55 Turbine Setting Out,” 2006.


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Appendix A. Drawings

Drawing Number Drawing Revision

Title 1 Title 2 Title 3 Document Reference

Electrical

RT019500-EEE-DG-0001 A Existing SLD Distribution and Generation

A.1

RT019500-EEE-DG-0003 A Proposed SLD Generation A.2

RT019500-EEE-DG-0005 A Proposed Protection SLD Generation A.3

Civil

RT019500-CCC-DG-0001 A Proposed Layout Overall Sheet 1 of 2 A.4

RT019500-CCC-DG-0002 A Proposed Layout Overall Sheet 2 of 2 A.5

RT019500-CCC-DG-0003 A Proposed Road and Hardstand

Solar and Wind Plan View – Sheet 1 of 2 A.6

RT019500-CCC-DG-0004 A Proposed Road and Hardstand

Solar and Wind Plan View - Sheet 2of 2 A.7

RT019500-CCC-DG-0005 A Proposed Road Solar and Wind Longitudinal Section A.8

RT019500-CCC-DG-0006 A Proposed Layout Power Station A.9

EXISTING SLDDISTRIBUTION AND GENERATION

NTS RT019500-EEE-DG-0001

LORD HOWE ISLAND BOARD

A

HYBRID RENEWABLE ENERGY PROJECT

A. NEWTONA 23.01.15 AN PRELIMINARY ISSUE

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DESIGN REVIEWDESIGNED

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ABN 37 001 024 095 and ACN 001 024 095Jacobs Group (Australia) Pty Ltd11th Floor, 452 Flinders StreetMELBOURNE, VIC 3000AUSTRALIA

Tel: +61 3 8668 3000Fax: +61 3 8668 3001Web: www.jacobs.com

PRELIMINARY ISSUE

PROPOSED SLDGENERATION

NTS RT019500-EEE-DG-0003 A




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LORD HOWE ISLAND BOARDHYBRID RENEWABLE ENERGY PROJECT

M.Y D.M.P D.M.P17/03/2015

A 17/03/2015 M.Y D.M.P PRELIMINARY ISSUE

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DATEREV DRAWN REVISION DRAWING NUMBER REFERENCE DRAWING TITLE

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ABN 37 001 024 095 and ACN 001 024 095

Jacobs Group (Australia) Pty Ltd

Ground Floor, 100 Melville Street

HOBART, TAS 7000

AUSTRALIA

Tel: +61 3 6221 3711

Fax: +61 3 6224 2325

Web: www.jacobs.com

PRELIMINARY ISSUE

PROPOSED LAYOUTOVERALLSHEET 2 OF 21:500 (A1) RT019500-CCC-DG-0002 A


M.Y D.M.P D.M.P17/03/2015


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HOBART, TAS 7000

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Tel: +61 3 6221 3711

Fax: +61 3 6224 2325

Web: www.jacobs.com

PRELIMINARY ISSUE

PROPOSED ROAD AND HARDSTANDSOLAR AND WINDPLAN VIEW SHEET 1 OF 21:500 (A1) RT019500-CCC-DG-0003 A


M.Y D.M.P D.M.P17/03/2015


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Fax: +61 3 6224 2325

Web: www.jacobs.com

PRELIMINARY ISSUE

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Tel: +61 3 6221 3711

Fax: +61 3 6224 2325

Web: www.jacobs.com

PRELIMINARY ISSUE

PROPOSED ROADSOLAR AND WINDLONGITUDINAL SECTION1:1000 (A1) RT019500-CCC-DG-0005 A


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Tel: +61 3 6221 3711

Fax: +61 3 6224 2325

Web: www.jacobs.com

PRELIMINARY ISSUE

PROPOSED LAYOUTPOWER STATION

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HOBART, TAS 7000

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Fax: +61 3 6224 2325

Web: www.jacobs.com

PRELIMINARY ISSUE


100

Appendix B. Glossary Term Meaning

Wind shear alpha value

A Weibull scale parameter

AEP Annual Energy Production

ASA Airservices Australia

ARENA Australian Renewable Energy Agency

BC AECOM 2014 Business Case [2]

BESS Battery Energy Storage System

the Board Lord Howe Island Board

BoM Australian Bureau of Meteorology

CAPEX Capital Expenditure

CF Capacity Factor

Ct Thrust coefficient

GHI Global Horizontal Irradiance

HREP Hybrid Renewable Energy Project

HV High Voltage

IEC International Electrotechnical Commission

k Weibull shape factor

kVA Kilovolt ampere

kVAr Kilovolt ampere reactive

kW / MW Kilowatt / Megawatt

kWh / MWh Kilowatt-hour / Megawatt-hour

kWpAC Kilowatt peak AC as measured at AC terminal of inverters

LHI Lord Howe Island

LHIB Solar The Lord Howe Island Board owned solar

LV Low Voltage

mAGL Metres Above Ground Level

mASL Metres Above Sea Level

MCP Measure Correlate Predict (wind analysis)

MEA Measurement Engineering Australia

OE Owners Engineer

OPEX Operational Expenditure

Option 1 Defined in Table 1.1

Option 2 Defined in Table 1.1

P50 Mean value or central estimate (statistics)

PoE Probability of Exceedance

Private Solar The Lord Howe Island privately owned solar

PV Photovoltaic

Renewable Penetration Defined in Section 9.3.5


101

Term Meaning

RMU Ring Main Unit

SCADA Supervisory Control and Data Acquisition

T01, T02 Turbine 01, Turbine 02

TI Turbulence Intensity

TI15 Turbulence Intensity at a 15 m/s 10 minute mean wind speed

U Mean average wind speed

WAsP Wind Atlas Analysis and Application Program

WTG Wind Turbine Generator

http://solargis.info/

http://www.nrel.gov/docs/fy12osti/51664.pdf

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