Line Upgrade Deferral Scenarios for Distributed Renewable Energy Resources

Distributed Energy Investment as an Alternative to Distribution Upgrades in Rural Areas

Dr. Iain Sanders Sustainable Innovative Solutions Limited of 25

Scenarios for Distributed Energy Investment as an Alternative to Distribution Line Upgrades in Rural Areas

By Iain Sanders, Sustainable Innovative Solutions Limited, and Alister Gardiner, Industrial Research Limited

Abstract In this paper, we identify and evaluate various ‘best-case scenarios’ for investing in decentralised micro-generation from a utility-driven, distribution network perspective. A distribution line experiencing significant over-capacity from increasing customer demand is used to determine the Net Present Value (NPV) of five different modular, distributed energy systems: (1) hydroelectric power (HEP) with diesel genset (DGN) support; (2) wind turbine generation (WTG) with DGN support; (3) photovoltaics (PVS) with DGN support; (4) solar hot water (SHW) with DGN support; and (5) DGN by itself, as a reference case. The study considers the value of distributed energy (DE) in deferring or eliminating distribution line energy- / capacity-based upgrades. The basic principle applied in this study is that the distributed generation installed consists of a combination of fuel-based (DGN) generation and intermittent renewable energy (RE) to ensure that “normal” supply reliability can be delivered at all times, irrespective of RE availability. Typical RE supply profiles are used to indicate the likely mix of RE and DGN supply throughout the year on a continuous half-hourly basis. The scale and format of the particular technologies is not specified, instead these are simply identified as opportunity costs. As a typical case study involving real “industry” data, the NPV of DE as a line upgrade deferral option was compared with a “business as usual” scenario for a rural distribution line in the Eastland Networks Limited (ENL) region of the north island of New Zealand. For the data presented in this report, the annual energy demand growth rate was exaggerated and extended over a 20-year timeframe to emphasize the potential contribution that DE could have on the energy / capacity supply mix for regions of high growth. The net results were almost always in favour of DE line upgrade deferral (as opposed to a “business as usual” network management arrangement) under the conditions assumed for this study. No attempt was made to account for any contributions of heat generated by the fuel based (diesel assumed) generation. Combined Heat and Power (CHP) would add substantial value by providing additional end use energy from the fuel resource.

Introduction Over the last nine years, Industrial Research has evaluated a wide range of resource opportunities for adopting Renewable Distributed Energy (RDE) technologies in New Zealand. The objective has been to evaluate and demonstrate the techno-economic viability of micro- (less than 100kW capacity), mini- (between 100kW and 1000kW capacity) and small-scale (between 1MW and 10MW capacity) RDE systems in New Zealand. In the process specialised tools and methodologies have been developed to fulfil this purpose. (Unless ‘scale’ is specifically mentioned, the term ‘small’ will refer to anything from micro-scale to small-scale inclusive). This research into distributed energy-based systems has been motivated by the promise of more efficient energy utilisation and the opportunity for capturing local renewable energy resources with minimal use of additional infrastructure. Specific network benefits are possible through: 1. Local generation solutions relieving distribution network capacity while maintaining utilisation (fig.1). 2. Technology that will provide alternatives to uneconomic network sections. 3. Creating the means for large numbers of small distributed generators to export aggregated



electricity from otherwise uneconomic network assets to different network users (see figure 2). 4. Ability to track slow growth in demand with small matching incremental steps in generation, thus

avoiding or delaying major upgrades. Figure 1: Local generation solutions to relieve peak distribution network capacity

Figure 2: Redesigning Distribution Networks Around Locally Available Distributed Energy Resources

Local distributed energy provides significant benefits to various stakeholders:

1. Support adoption of environmentally friendly energy supply alternatives; 2. Provide supplementary revenue for farmers – other network customers; 3. Reduce burden of long-term infrastructure upgrades on network customers;

Predicted Load Duration Curve

TypicalExample

What is Line Upgrade Deferral?

MainPower Lyndon (ML) line

2 0 0 3 L o a d D u r a t io n C u r v e fo r L y n d o n L in e

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39

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66

24

92

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65

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C u m m u la t iv e H o u r s o f t h e Y e a r

Ca

pa

cit

y (

kW

) 6 0 k W B A S E - C A S E U S E D F O R L O A D D U R A T IO N P R O J E C T I O N S

8 0 k W M A X I M U M S T A N D A R D O P E R A T I N G C A P A C I T Y T H R E S H O L D


0

1 0

2 0

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66

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92

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Ca

pa

cit

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kW



Firm DE

Primary objective for DE to meet peak load requirements





0

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Ca

pa

cit

y (

kW




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1 0

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92

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pa

cit

y (

kW



Firm DE



0

1 0

2 0

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86

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66

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Ca

pa

cit

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kW




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1 0

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11

33

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60

15

86

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13

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39

22

66

24

92

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19

29

45

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72

33

98

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78

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45

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58

90

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63

43

65

69

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72

49

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28

81

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81

86

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Ca

pa

cit

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kW



Firm DE


0

1 0

2 0

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66

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08


Ca

pa

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kW




0

1 0

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3 0

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1 0 0

1

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7

45

4

68

0

90

7

11

33

13

60

15

86

18

13

20

39

22

66

24

92

27

19

29

45

31

72

33

98

36

25

38

51

40

78

43

04

45

31

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57

49

84

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10

54

37

56

63

58

90

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63

43

65

69

67

96

70

22

72

49

74

75

77

02

79

28

81

55

83

81

86

08


Ca

pa

cit

y (

kW



Firm DE


C u s t o m e r E f f i c i e n c y

C e n t r a l G e n e r a t i o n

T o d a y ' s T o d a y ' s C e n t r a l U t i l i t yC e n t r a l U t i l i t y

T o m o r r o w ' s T o m o r r o w ' s D i s t r i b u t e d U t i l i t y ?D i s t r i b u t e d U t i l i t y ?

R e m o t eL o a d s

W i n d

P V

G e n s e t

F u e l C e l l

B a t t e r y

C u s t o m e r s

C e n t r a l G e n e r a t i o n

© 2 0 0 2 D i s t r i b u t e d U t i l i t y A s s o c i a t e s1

M i c r o t u r b i n e

Can Costly Upgrades Be Prevented?



4. Reduce risk of failure of overloaded transmission and distribution lines, and potentially increase system security;

5. Promote supply energy-efficiency; 6. Only invest in what is required using modular distributed energy (DE) technologies; and, 7. Potentially provide additional revenue / savings for network operators.

Using integrated distributed energy technologies, some technologies may be owned and controlled by the networks, and some technologies may be owned and controlled by the customers. These potential network benefits contrast with the more popular view that distributed generation threatens the traditional electricity supply infrastructure by taking away energy delivery but not alleviating capacity demands. Note that the network benefits are case specific, and are primarily based on demand growth scenarios. Previous work by Industrial Research has identified few if any benefits accruing to distribution networks from distributed generation in regions with static or declining load. In the main, small-scale technology developers have been preoccupied with reducing the costs of their own particular product in the high volume micro- / mini-scale embedded generation marketplace. Unfortunately, no single technology can yet provide the quality of service delivered by the distribution network, at the distribution network price. For example, a wind generator cannot guarantee firm capacity, so the network must provide this; and, while a diesel genset can deliver capacity the cost of energy from a diesel genset is generally too high, so it is relegated to a standby function. This paper evaluates the ability of combinations of local resources to deliver matching energy and firm capacity to complement grid based electricity services, and the value accrued from offsetting investment costs associated with local growth.

Background of Research Industrial Research Limited (IRL) has worked with Eastland Networks Limited (ENL) support to evaluate the potential economic impact of Distributed Energy Resources (DERs) on the East Coast potion of their distribution network (see figure 3). This was chosen as typical of rural network asset Figure 3: East Coast Portion of Eastland Networks Limited

Main Case Study – a section of the Eastland Network was chosen –

The Ruatoria 11kV Feeder from the Ruatoria 50/11kV Substation

Eastland Network

Te Puia is fed from

Tokomaru Bay

50/11kV line

TOLAGA BAYINPORT

TOKOMARU BAY INPORT

RUATORIA INPORT

TE ARAROAINPORT

GISBORNEINPORT

FOCUS





Eastland Network

Te Puia is fed from

Tokomaru Bay

50/11kV line

TOLAGA BAYINPORT

TOKOMARU BAY INPORT

RUATORIA INPORT

TE ARAROAINPORT

GISBORNEINPORT

Te Puia is fed from

Tokomaru Bay

50/11kV line

TOLAGA BAYINPORT

TOKOMARU BAY INPORT

RUATORIA INPORT

TE ARAROAINPORT

GISBORNEINPORT

FOCUS



conditions and costs, because of the limited availability of detailed asset valuation. The East Coast portion of the Eastland Network stretches from Gisborne in the south to Hick’s Bay in the north. A single 50kV subtransmission line carries electricity from Gisborne up the coast to four substations at: 1. Tolaga Bay, 2. Tokomaru Bay, 3. Ruatoria, and 4. Te Araroa (see figure 3). These four substations deliver power to the communities on the East Coast via 14 11kV feeders (see figure 4). The 11kV feeders distribute electricity to the communities and individuals in the region.

Figure 4: Eastland Network’s East Coast feeders and substations

Motivation for the Research It is getting harder for electricity distribution networks to cover their O&M and replacement costs on infrastructure for the following reasons:

1. Increasing or remote rural population hot spots putting pressure (often seasonal) on existing rural networks (although this reason is not particularly relevant to the East Coast region);

2. Most rural network infrastructure is old, nearing the end of its normal life, making O&M costly and in need of replacement; and,

3. Routine preventive O&M is less affordable, resulting in more severe and costly failures when they happen.

New Zealand is rich in alternative energy resources which could make a substantial contribution towards meeting the country’s future energy demand through DE grid-support projects. At present however, these generation technologies are hard to justify on a purely user “demand side” basis. If treated as a “supply side” asset, (as they potentially are via the right to connect) the economic case can improve dramatically. There is substantial potential for DE technologies to reduce peak demand and hence extend the life of New Zealand’s ageing network infrastructure. These opportunities may be extended in the future to automatic islanding and self-healing interactive micro-grids delivering higher reliability at lower service costs. Furthermore, local communities are keen to develop natural

FROM 1ST SUBSTATION:

FEEDERS A, B, C & D

FROM 2ND SUBSTATION:

FEEDERS E, F & G

FROM 3RD SUBSTATION:

FEEDERS H, I, J & K

FROM 4TH SUBSTATION:

FEEDERS L, M & N

TE ARAROASUBSTATION

RUATORIASUBSTATION

TOKOMARU BAYSUBSTATION

TOLAGA BAY SUBSTATION

FROM 1ST SUBSTATION:

FEEDERS A, B, C & D

FROM 2ND SUBSTATION:

FEEDERS E, F & G

FROM 3RD SUBSTATION:

FEEDERS H, I, J & K

FROM 4TH SUBSTATION:

FEEDERS L, M & N

TE ARAROASUBSTATION

RUATORIASUBSTATION

TOKOMARU BAYSUBSTATION

TOLAGA BAY SUBSTATION



resources for long-term sustainable development or as part of locally-sponsored sustainability initiatives and programs. Providing that the regulatory and market environment is adapted to recognize the benefits, these technologies will transform many aspects of network power in the future.

Methodology of the Study In this study, three load growth scenarios representing a 1.5%, 5% and 10% increase in peak load per year for 20 years were selected and used to demonstrate the potential value from deferring infrastructure line upgrades, by using supplementary distributed energy to provide the peak load shortfall whenever the physical limit of the distribution line was exceeded. The peak load shortfall was calculated both as a capacity shortfall (in kW) and an energy shortfall requirement (in kWh), so that the line upgrade deferral value (of investment in network infrastructure capacity to meet the peak load shortfall) could be measured as a Net Present Value (NPV) marginal distribution capacity cost (MDCC) in $/kW/year (known as the capacity-valuation method), and as a NPV marginal distribution energy cost (MDEC) in $/kWh (known as the energy-valuation method). The peak load capacity / energy shortfall requirement was determined by selecting an appropriate capacity threshold (i.e. physical upper limit of feeder capacity supply) for the distribution feeder meeting the demand. In this report, we cover the 10% annual load growth scenario, and show how distributed energy can be used to reliably meet the capacity / energy shortfall resulting from demand outstripping the capability of a network feeder to supply all the capacity / energy required. Capacity / energy shortfalls from surplus demand were addressed by a combination of renewable (in this case: hydroelectric, wind, photovoltaic and solar hot water) and fuel-driven (in this case diesel) distributed energy. Ratios of 80%/20%, 50%/50% and 20%/80% RE/DGN were used, and these ratios represent the proportion of capacity delivered by the RE and DGN components when 100% of the RE capacity is available. If the peak capacity shortfall is 100kW for example, for a 50%/50% WTG/DGN system, 50kW of WTG is the maximum capacity contribution from the wind (and the assumed name plate sizing of the turbine) with the peak capacity shortfall balance of 50kW met by the diesel genset. The capacity and energy shortfall requirements were calculated on a half-hourly basis over a 20-year period for each of the load growth scenarios. These figures were converted into monetary values using the network asset valuation reports to derive an annual financial contribution requirement to operate, maintain and replace the existing feeder. The annual financial contribution to line upgrade / replacement was discounted to provide the NPV marginal distribution cost introduced previously. The total capacity and energy benefit derived from the various combinations of distributed energy (DE) used, covered: (a) line upgrade deferral using RE and DGN; (b) peak distribution capacity shortfall (wholesale) energy contributions from RE and DGN; (c) off-peak (wholesale) energy contributions from RE (don’t want to waste non-peak RE available); (d) transmission peak load reduction at the grid exit point (GXP) from RE and DGN capacity contributions. These benefits were offset by the capital and O&M costs (including fuel costs) associated with using different DE combinations, and the loss in network energy distribution revenue caused by using local DE to meet the demand instead of energy imported from the GXP. The net benefit / cost was derived from the difference between these amounts, and the return on investment (ROI) was derived from the ratio of these amounts. The economic assumptions are summarized below in table 1: Table 1: Key Economic Assumptions for DE Benefits and Fuel Costs

Line Upgrade Deferral Value (Capacity-valuation method, MDCC) $99.37/kW/Year Line Upgrade Deferral Value (Energy-valuation method, MDEC) $0.0807/kWh GXP Transmission Savings Value $50.62/kW/Year Energy Wholesale Price $0.1289/kWh Energy Distribution Revenue Loss $0.0687/kWh Diesel Fuel Price and Annual Increase Range $1-$3.00/litre, 2-10%/Year increase



Ruatoria Feeder Case Study The Ruatoria feeder (see figure 4) on the Ruatoria substation (see figure 3) was selected for this study (see figure 5). This feeder was selected because it demonstrated an annual increase of peak capacity, and detailed asset management information along with half-hourly demand information was available.

Figure 5: Ruatoria Feeder Half-hourly Capacity Profiles for 2001-2003

Load Profile History and Projections The local load profiles are used to enable prediction of DE capacity support opportunities. For three years in succession, 2001 to 2003, the average peak capacity growth rate was 1.5% / year. To better

Figure 6: Ruatoria Load Growth Scenarios Adopted

Comparison of Peak Load Growth Scenarios and Relationship to the Capacity Threshold for Grid-

Support on the Ruatoria Feeder

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Time in Years

To

tal L

oad

(kW

)

Threshold

1.75% / Yr

5% / Yr

10% / Yr

PEAK LOAD DE REQUIREMENT

FOR 5%/YR GROWTH


FOR 10%/YR GROWTH

PEAK LOAD DE REQUIREMENT FOR 1.75%/YR GROWTH

Comparison of Peak Load Growth Scenarios and Relationship to the Capacity Threshold for Grid-

Support on the Ruatoria Feeder

0

1,000

2,000

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9,000

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oad

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5% / Yr

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PEAK LOAD DE REQUIREMENT FOR 1.75%/YR GROWTH



illustrate the potential impact of DE on line upgrade deferral for the more general case, growth projections of: 1.75, 5 and 10% / year were investigated. A peak capacity threshold of 1,600kW was selected to illustrate the methodology used, although the exact capacity constraints were not identified. The capacity threshold represents the capacity above which the feeder is overloaded due to voltage drop, overheating or overloading etc. (see figure 6). We have assumed that the demand profile and load factor do not change over this growth period. Detailed analysis presented here gives the results obtained for the 10% load growth scenario to emphasize the potential impacts of DE technologies.

Assessing Costs of Network Upgrades In order to derive the benefit available from installing DE to meet the peak load requirement when the threshold capacity of the Ruatoria Feeder is surpassed (1,600kW for the purposes of this case study), it is necessary to calculate the line upgrade deferral value of the feeder. The line upgrade deferral value is calculated by combining the direct and indirect annual O&M costs of the feeder with the hypothetical cost of reinvestment once existing infrastructure is replaced. The following information has been provided by ENL, based upon ENL network data and ENL assumptions made.

The total annual investment required to maintain and upgrade the Ruatoria Feeder has been calculated to be $74,028. This value was converted into NPV $/kW/year and $/kWh/year amounts, corresponding to the annual energy and capacity demand forecasts predicted over a 20-year timeframe for a 10% annual growth rate. The marginal distribution capacity and energy costs (MDCC and MDEC) are summarized below in table 2: Table 2: Key Parameters and Assumptions for Marginal Distribution Capacity and Energy Costs

Parameters Value Feeder Capacity Threshold, C(T) 1,600kW Network Finite Planning Horizon, n 40 Years

Note 1

(Max.) Network Investment Deferral Period, D(t) 20 Years Note 2

Unity Cost of Capital (Borrowing), r 10% Inflation Rate Net of Technology Progress, i 3% Baseline Diesel Fuel Price and annual increase $1.00/litre (Yr-0), 2%/yr inc. Capacity Deferred by D(t) Years 6,473kW NPV Marginal Distribution Cost (MDC) $739,063.44 NPV MDCC / kW / Year $99.37 / kW / Year NPV MDEC / kWh $0.0807 / kWh Net Present Cost of Feeder Distribution / Customer / Day $0.609

Note 3

Note 1: Planning Horizon = Furthest extent of asset investment (max. possible in the model is 100 years). Note 2: Deferral Time = Duration of DE project (1 to 30 years (max.) possible). Note 3: This cost does not include the share of the 50kV subtransmission which is included in the total distribution cost. Because our DE options do not effect this cost component, it has not been used in the comparisons.

Direct & Indirect Annual O&M Costs (Derived from ENL Asset Management Plan and ENL Asset Accounting Spreadsheets)� Direct Costs = $935 / km / Year

� Indirect Costs = $66 / Connection / Year

Estimated cost of reinvestment once existing infrastructure is replaced (as assessed by ENL)� Annual reinvestment cost = {ODRC x 2} / 40 (lifetime)

� ODRC = Optimized Depreciation Replacement Cost

333

No. of Connections

$40,678.0020.000Ruatoria: H. Ruatoria

Annual O&M CostsLength (km)FEEDER

333

No. of Connections

$40,678.0020.000Ruatoria: H. Ruatoria

Annual O&M CostsLength (km)FEEDER

Total Return = Annual O&M Costs + Annual Reinvestment

$40,678.00

Annual O&M Costs

$74,028.00$33,350Ruatoria: H. Ruatoria

Total Annual RequiredReinvestment / Yr.FEEDER

$40,678.00

Annual O&M Costs

$74,028.00$33,350Ruatoria: H. Ruatoria

Total Annual RequiredReinvestment / Yr.FEEDER



Assessing Costs of Network Upgrades The values in the list above for the net present value marginal distribution capacity and energy cost (NPV MDCC and NPV MDEC): $99.37/kW/year and $0.0807/kWh/year, compare reasonably well with data from other sources and represent the value per unit capacity and energy per year of deferring distribution network upgrade by a year via reliable DE peak capacity / energy network-support. There are however, costs to the network from introducing reliable DE, and these will reduce the net benefits of line upgrade deferral. The assumed DE capital and operating (fuel and maintenance) costs are summarized in figure 7 below and table 2 above. The costs of DE necessary to match the system capacity shortfall were derived from the total capacity shortfall using figure 7. The quality of results delivered with the model are dependent on the level of detail provided by the load profile projections, RE supply profiles and other input parameters required. The higher the detail, the better the accuracy of the costs predicted. In this study the renewable energy (RE) and diesel genset (DGN) supply curves were derived from half-hourly time sequence data derived for a complete year. These curves are used to establish the amount of DGN and RE generation capacity required to maintain supply service as the demand grows, without network capacity extensions. That is, local DE supply was used to support the capacity / energy shortfall when capacity / energy demand surpassed the Ruatoria Feeder’s threshold value as identified in table 2. RE was always the preferred local DE supply option selected to make up for the peak load shortfall, with the fuel-driven DGN making up the balance. The capital costs assumed for the individual modular units used in the five DE scenarios selected:

(1) hydroelectric power (HEP) with diesel genset (DGN) support; (2) wind turbine generation (WTG) with DGN support; (3) photovoltaics (PVS) with DGN support; (4) solar hot water (SHW) with DGN support; and (5) DGN by itself, are shown in figure 7.

Figure 7: Assumed DE Capital Costs

The modular capacity profiles of the RE resources used in this study (the four RE resources used in

Hydro & Wind Capital Cost: O&M = 2% of Capital Cost / Year

PV & SHW Capital Cost: O&M = 0.5% of Capital Cost / Year

Diesel Genset Capital Cost: O&M = 5% of Capital Cost / Year

$100

$1,000

$10,000

$100,000

0 1 10 100 1,000 10,000

Size, kW

Cap

ital C

ost, $

/kW

Hydro

Wind

Photovoltaic

Solar Hot Water

Genset

Log. (Photovoltaic)

Log. (Hydro)

Log. (Wind)

Log. (Solar Hot Water)

Log. (Genset)



the five DE scenarios mentioned previously) are shown in the following graphs. With the exception of HEP, the supply profiles (see figures 10-12) were adjusted by scaling to the peak capacity shortfall. The HEP profiles were derived differently, because the volume of water available in the flow-of-river resource was fixed (se figure 8).

Figure 8: First Six Months’ Half-Hourly Flow-of-River Hydro Resource Used in the Study

The HEP supply factor corresponding to the flow-of-river resource used (see figure 8) was related to the HEP turbine capacity rating (see figure 9). Figure 9: HEP Supply Factor for Flow-of-River Used

The HEP supply curve in figure 9 shows the relationship between the average capacity delivered to the actual turbine capacity rating, based upon the maximum capacity available for extracting from the

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ating)



river. If for example, the river can deliver a maximum capacity of 10MW for 2 weeks of the year, and the HEP turbine rating is 1MW, the average HEP supply capacity available is 0.6 x 1MW = 600kW. The first six months’ WTG supply profile for a 1MW turbine is shown in figure 10 below. This profile assumes an average annual wind speed of 6m/s. Figure 10: WTG First Six Months’ Half-Hourly Profile

Figure 11: PVS First Six Months’ Half-Hourly Profile

The first six months’ PVS half-hourly profile for a 1kW system is shown in figure 11. The profile used was derived from best fit solar data for the East Coast region and also applied to produce the SHW

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of a Normal Calendar Year (Annual Wind Speed = 6m/s)

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)

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ear /...

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of a Normal Calendar Year

0.00-0.10 0.10-0.20 0.20-0.30 0.30-0.40

0.40-0.50 0.50-0.60 0.60-0.70 0.70-0.80

0.80-0.90 0.90-1.00



profile in figure 12. The solar hot water profile is significantly different to the PVS profile because it is assumed that electrical water heating (the load that is replaced by SHW) takes place during the off-peak period: 11pm to 7am (used in ripple-relay control of domestic water cylinders in many parts of New Zealand). This would not be the case for all time periods in the year, but is an adequate approximation because it would certainly be the case during peak load periods. Figure 12: SHW Contribution to Electrical Heating Demand

It is worth mentioning at this point the quite negative impact that SHW investment has on network costs. SHW results in lower energy sales for the same network capacity requirements. This can be substantial since water heating represents 25-35% of residential energy demand. As identified in the introduction, a basic principle for the analysis is that DE must provide the same level of reliability as network supply. Thus is achieved by matching the capacity requirement one for one with fueled generation (DGN), irrespective of the level of intermittent renewable technology installed. The five DE scenarios selected: (1) hydroelectric power (HEP) with diesel genset (DGN) support; (2) wind turbine generation (WTG) with DGN support; (3) photovoltaics (PVS) with DGN support; (4) solar hot water (SHW) with DGN support; and (5) DGN by itself; matched continuous half-hourly energy demand with the supply available from each of these scenarios. The net cost-benefit of each of these DE scenarios on the Ruatoria Feeder for line upgrade deferral was determined. The following DE costs were included: capital investments, maintenance, operating costs and fuel costs etc. to calculate the net present value (NPV) of both the renewable and fuel-based DE options. The following DE benefits were included (as introduced in table 1) to calculate the NPV of both the renewable and fuel-based DE options.

• line upgrade deferral: $99.37/kW/Year or $0.0807/kWh/Year; • transmission savings: $50.62/kW/Year peak GXP load reduction;

0:001:00

2:003:00

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JanFeb

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AprMay

JunJul

AugSep

OctNov

Dec

0

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1

1.5

2

kW

Ele

ctr

ical H

ot

Wate

r E

qu

ivale

ntTime of Day

Month of Year

Heating Profiles Contributed by a 4m2 Solar Hot Water System

0-0.5 0.5-1

1-1.5 1.5-2



• grid-supporting energy production: $0.1289/kWh; and, • non-grid-supporting energy production ($0.1289/kWh/Year)

less loss of distribution earnings ($0.0687/kWh/Year) to the network from using local energy. NPVs were calculated over a 20-year project lifecycle, assuming a 10% utility cost of capital interest rate, and a 3% inflation rate net of technology progress. The RE-DGN mix was fixed at the following peak capacity (name plate rating) ratios in this study: 1. 20%/80% DGN/RE, 2. 50%/50% DGN/RE, 3. 80%/20% DGN/RE, and 100% DGN (scenario five). The RE generation capacity was selected to ensure it met 20, 50 or 80% of the peak load shortfall when delivering 100% of its name plate capacity rating (sizing).

Alternative Line Upgrade Deferral Methodologies Two different line upgrade deferral valuation methodologies were used in this study to calculate the NPV derived from DE technologies: capacity and energy. Both methods calculated the network capacity requirements from DE for every half-hour over a 20-year period. Method 1: capacity valuation – values the line assets or any alternative generation (DE) options – based upon the peak (maximum) capacity delivered by the assets each year; and, method 2: energy valuation – values the line assets or any alternative generation (DE) options – based upon the total (sum) energy delivered by the assets each year. The net lifetime benefit from each method for line upgrade deferral is compared in figure 13. Figure 13: Comparison of Capacity Valuation (Method 1) and Energy Valuation (Method 2) for Line Upgrade Deferral

Figure 13 shows that the dominant value from DE in this situation is for line upgrade deferral, representing 78% for capacity valuation and 85% for energy valuation. The difference in value is attributed to the difference in impact of NPV discounting on the variation in energy and capacity benefits during the 20-year line upgrade deferral project lifetime. A substantial increase in energy value from line upgrade deferral in latter years is not offset by NPV discounting to the same degree as the capacity value. The NPV of capacity-driven line upgrade deferral benefits is greater in the early years, while the NPV of energy-driven line upgrade deferral is greater in the latter years. Overall, the energy NPV over the 20-year project lifetime is greater than the capacity NPV.

Comparison of Net Benefit from Capacity-Driven vs. Energy-Driven Line Upgrade Deferral

-$2,000,000

-$1,000,000

$0

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$3,000,000

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kW-Focus kWh-Focus

NP

V for

Lifetim

e B

enefi

t

Disc. Distribution (kWh)

Disc. Grid-Supporting Energy (kWh)

Disc. Trans. Saving (kW)

Disc. Upgrade Deferral (kW)

Line upgrade deferral value based on kW capacity valuation methodology

Line upgrade deferral value based on kWh energy valuation methodology

Relates to energy supplied only during peak

periods related to grid-support

Distribution feeder peak load

reduction corresponding to

GXP peak load reduction

Distribution revenue lost

Peak period kW capacity valuation for line

upgrade deferral

Peak period kWh

energy valuation for line

upgrade deferral

Comparison of Net Benefit from Capacity-Driven vs. Energy-Driven Line Upgrade Deferral

-$2,000,000

-$1,000,000

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e B

enefi

t

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Disc. Grid-Supporting Energy (kWh)

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Line upgrade deferral value based on kW capacity valuation methodology

Line upgrade deferral value based on kWh energy valuation methodology

Relates to energy supplied only during peak

periods related to grid-support

Distribution feeder peak load

reduction corresponding to

GXP peak load reduction

Distribution revenue lost

Peak period kW capacity valuation for line

upgrade deferral

Peak period kWh

energy valuation for line

upgrade deferral



It has been observed that method 1: capacity valuation, is more beneficial to fuel-driven DE systems with low capital costs (i.e. DGN by itself), and method 2: energy valuation is more beneficial to RE-driven DE systems with unpredictable delivery of capacity needs. Capacity valuation benefits fuel-driven DE systems more because energy is only provided to supply capacity needs for peak load reduction. Peak load reduction may typically involve long narrow (sharp) spikes with little energy content. This scenario is ideal for network companies operating diesel gensets for only a few hours of the year. Energy valuation is better for customer-driven renewable energy contributions that cannot be switched on and off “on tap” like a standby generator. Energy valuation notes and values the aggregate contribution of individual RE options over the year when capacity-support from a particular RE technology may vary anywhere between 0 and 100% for different (peak load) time periods.

Results from the Ruatoria Feeder Case Study A comparison of the RE-DGN cost-benefits is given in figure 14 below, with the NPV benefits shown in blue besides the NPV costs shown in red for each scenario investigated. The bar chart shows the RE costs / benefits on top (brighter colours) of the DGN costs / benefits (lighter colours). Figure 14: RE-DGN Cost-Benefit Analysis

Figure 14 shows that for this baseline case of low fuel inflation (2%/year), the greater the DGN component in the total RE-DGN mix, the lower the NPV lifecycle cost of the system installed. Only two DE systems are shown to make a net loss: the 20%/80% DGN/PVS and the 50%/50% DGN/PVS, due to the large capital costs incurred with installing the PVS system (see figure 7). Figure 15 compares the annualized Return on Investment (ROI) from having invested in the different RE-DGN combinations shown in figure 14 above. Figure 15 shows that under current costs for operating gensets in New Zealand (assuming a $1.00/litre price for diesel (or any other fuel producing the same electrical output), increasing at an average fixed rate of 2% per year), scenario 5: DGN by itself (0%/100% RE/DGN) represents the most beneficial option for DE line upgrade deferral on the Ruatoria Feeder. While renewable DE without carbon credits appears to be less attractive than diesel generation, distributed renewable energy (RDE) coupled with firm capacity from fuel-based generation such as diesel gensets (DGN) still offers a substantial strategic benefit over conventional expansion of the

Comparison of Net-Benefits and Net-Costs from Various RE-Genset Combinations

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ost

Renewable Benefit – Cost of distribution revenue loss

Genset Benefit – Cost of distribution revenue loss

Renewable Cost

Genset Cost

Comparison of Net-Benefits and Net-Costs from Various RE-Genset Combinations

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Renewable Cost

Genset Cost



network supply system capacity in the demand growth scenario. Comparison of the difference in NPV between any combination of DGN/RE and the base-case of DGN alone (last 2 columns of figure 14) shows the cost of adopting various strategic options to increase the amount of renewable electricity by this approach. From figure 15 it can be seen that the value of the contribution of RE to the total DE contribution varies with different technologies as shown in figure 16. Both the costs and the benefits of the RE portion of the investment are plotted against the percentage of renewables present. This data is taken from the RE only portion of the bar graphs in figure 14. Figure 15: RE-DGN Annualized ROI

Figure 16: RE-only Cost-Benefit Analysis for Various RE-DGN ratios

In every case bar one (HEP-DGN benefit scenario), the net benefit / cost increases when the RE component increases. Net benefit increases because more energy is delivered, and the average

Annualised Return on Investment (ROI) from Investing in Different RE-Genset Combinations

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fit

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ro B

enefit

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ro B

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enefit

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Benefit

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ro B

enefit

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ind Benefit

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nnualised o

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ears

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Net Benefit

Net RE Cost-Benefit from Different Renewable Ratios in the Genset-Renewable DE Mix

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Net C

ost-B

enefit in

NP

V (O

ver 20 Y

ears

)

Hydro-Benefit

Wind-Benefit

PV-Benefit

SHW-Benefit

Hydro-Cost

Wind-Cost

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SHW-Cost

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Cost

Net RE Cost-Benefit from Different Renewable Ratios in the Genset-Renewable DE Mix

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ost-B

enefit in

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SHW-Benefit

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capacity supplied is increased. The net cost increases because the size of the HEP, WTG, PVS or SHW system increases, and the capital cost is directly proportional to the name plate capacity rating of each RE system. However, overall, the % ROI reduces for a larger investment in renewables because small scale renewables at present show a lower ROI than diesel gensets. This is the cost one must pay if wishing to maintain or increase the renewable component of a strategic DG policy. The HEP-DGN benefit scenario in figure 16 is unusual, in that at about 50%/50% HEP/DGN the return becomes negative (cost is greater than the benefit). The explanation for this is tied to the HEP supply factor graph given in figure 9. The larger HEP system in figure 16 has a lower supply factor (see figure 9), implying that less peak capacity is available to match the peak demand required for line upgrade deferral.

Figure 17: Combined RE-DGN Cost-Benefit Analysis for Various RE-DGN ratios

The PV scenarios show negative financial benefit for all ratios, as do the SHW scenarios. Only the wind scenarios show a positive financial benefit for all levels of penetration. The negative SHW benefit may appear odd. This analysis however, is only for the benefit of avoiding network upgrades. The energy value to the owner is not included. Hence, because SHW is assumed to offset a controlled load (electric hot water storage heating) this analysis illustrates a very important outcome: SHW investment will not reduce the need for network investment in regions of demand growth. Figure 17 contains the combined RE-DGN cost-benefits derived for the different ratios examined. The DGN cost / benefit component makes up the balance of the RE results given in figure 16 and has the effect of smoothing out the NPV change between different percentages of RE in the combined RE-DGN system. The NPV of energy delivered for line upgrade deferral (refer to figure 13 for comparison with the capacity valuation method), transmission savings at the Grid Exit Point (GXP), wholesale energy sold (providing grid-support) and loss of distribution earnings, were calculated and compared for each year, using 100% DGN as the base case (scenario 5). Figure18 shows the NPV energy valuation time-series for line upgrade deferral for scenario 5: 100%/0% DGN/RE with a 10% / year peak load growth scenario. The other DE systems with a RE component: scenarios 1-4, also include a NPV of surplus wholesale

Net DE [RE+Genset] Cost-Benefit from Different Renewable Ratios in the Genset-Renewable DE Mix

$0

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Net C

ost-B

enefit in

NP

V (O

ver 20 Y

ears

)

Hydro-DE Cost

Wind-DE Cost

PV-DE Cost

SHW-DE Cost

Hydro-Benefit

Wind-Benefit

PV-Benefit

SHW-Benefit

Benefit

Cost

Net DE [RE+Genset] Cost-Benefit from Different Renewable Ratios in the Genset-Renewable DE Mix

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Net C

ost-B

enefit in

NP

V (O

ver 20 Y

ears

)

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Wind-DE Cost

PV-DE Cost

SHW-DE Cost

Hydro-Benefit

Wind-Benefit

PV-Benefit

SHW-Benefit

Benefit

Cost

Benefit

Cost



energy sold and loss of distribution earnings not related to line upgrade deferral. Surplus wholesale renewable energy sold corresponds to the energy produced by the RE system throughout the year that doesn’t correspond to the peak load reduction periods mentioned in figure 6. Furthermore, this energy corresponds to a loss in revenue to the network company that would have delivered the same amount of energy to the end-user from the Grid-Exit-Point (GXP) instead of through locally available renewable distributed energy. This is the component of renewable energy produced during non-peaking times, which it is assumed in this study does not attract any line charge and therefore replaces energy which would otherwise be conveyed over the network for a fee. Figure 18: 100%/0% DGN/RE Net Benefit Per Year Over Lifetime

Differences Between Capacity Valuation and Energy Valuation Methods Despite greater discounting of long-term capacity / energy benefits, the overall (summation) financial benefit of the discounted kWh energy valuation methodology (see figure 13) was greater than the financial benefit derived from the discounted kW capacity valuation methodology. This implies minimum-cost (financial outlay) for network-operated DE with capacity-driven valuation (for example: large-scale DE capacity installation with Orion Networks); and, maximum-benefit for customer-operated DE with energy-driven valuation (for example: small-scale DE energy installation with Orion Networks). In reality there is an optimum between the two approaches used: network cost-reduction versus customer value-creation, because smaller systems are more capital intensive (greater cost per unit kW / kWh supplied) and costly to operate and maintain per kW / kWh supplied.

Time-Series DGN-RE Scenarios for the 50%/50% DGN/RE Ratio Mix A comparison of different renewable (RE) to fuel-driven (DGN) ratios was made based upon the actual kW sizing (name plate) of each individual RE and DGN system. The annual installation of DE capacity over the 20-year lifecycle selected, matched the shortfall in the distribution system capacity for the Ruatoria Feeder. Note that these graphs give the grid-support capacity value from the various energy production components, not the value of energy itself. This study examined the results for: 100%/0%, 80%/20%, 50%/50% and 20%/80% DGN/RE ratios. The results for the 50%/50% DGN/RE ratio mix are presented below for discussion.

Line Upgrade Deferral Met By 100% Genset and 0% Renewable (RE)

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$1,500,000

$1,600,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

No. of Years Line Upgrade Deferred

Net P

resent V

alu

e o

f N

et A

nnual D

E B

enefit

Gen Distribution Loss

Gen Grid-Supporting Energy

Gen Trans. Saving

Gen Upgrade Deferral

Peak period kWh energy valuation for line upgrade

deferral

Line Upgrade Deferral Met By 100% Genset and 0% Renewable (RE)

-$200,000

-$100,000

$0

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

$800,000

$900,000

$1,000,000

$1,100,000

$1,200,000

$1,300,000

$1,400,000

$1,500,000

$1,600,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20


Net P

resent V

alu

e o

f N

et A

nnual D

E B

enefit



Gen Trans. Saving



deferral


deferral



Energy and Capacity Contributions of the 50%/50% DGN/RE Ratio Mix

The following graphs (figures 19 to 22) represent the energy and capacity (grid-support in equivalent kWh supplied) contributions provided by the renewable and non-renewable (i.e. DGN) components of the 50%/50% DGN/RE ratio mix for grid-support. In every case, DGN provides the energy and capacity shortfall not available from the RE-component (HEP, WTG, PV and SHW). These graphs can be compared with the Net Present Values (NPV) of the overall DE (DGN+RE) benefits delivered per year for each of the four 50%/50% DGN/RE ratio scenarios examined in the next section (see figures 23 to 26).

Energy Supplied from Various Sources using HEP

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Year

kW

h / Y

ea

r

RE Non Grid-Support kWh

Genset Grid-Support kWh

RE Grid-Support kWh

Grid Supplied kWh

Figure 19: 50%/50% DGN-HEP Grid-Support and Additional Energy Contributions in kWh / Year

Energy Supplied from Various Sources using WTG

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Year

kW

h / Y

ea

r



RE Grid-Support kWh

Grid Supplied kWh

Figure 20: 50%/50% DGN-WTG Grid-Support and Additional Energy Contributions in kWh / Year



Figures 19 to 22 show that non grid-support energy contributions are significantly higher with HEP (figure 19) than with the other RE resources (figures 20-22). The non grid-support energy contributions represent the surplus energy supplied by the alternative RE resources that do not contribute to peak load reduction: i.e. do not reduce the peak load required from the grid to meet demand.

The non grid-support energy contributions from the WTG and SHW components are almost identical, despite the fact that SHW grid-support is negligible when compared directly with that supplied by the WTG. Although the non grid-support energy supplied by PV is negligible, PV’s overall contribution is greater than SHW when grid-support is taken into consideration. Grid-support energy is valued

Energy Supplied from Various Sources using PV

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Year

kW

h / Y

ea

r



RE Grid-Support kWh

Grid Supplied kWh

Figure 21: 50%/50% DGN-PV Grid-Support and Additional Energy Contributions in kWh / Year

Energy Supplied from Various Sources using SHW

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Year

kW

h / Y

ea

r



RE Grid-Support kWh

Grid Supplied kWh

Figure 22: 50%/50% DGN-SHW Grid-Support and Additional Energy Contributions in kWh / Year



substantially higher than non grid-support energy, as illustrated by comparing the NPV of energy supplied by PV (figure 25) and SHW (figure 26). Despite the fact that grid-support and non grid-support energy contributions from PV are less than those from WTG, there is still a significant contribution from PV, due to the close match between the solar energy profile supplied and the peak load of the Ruatoria feeder needing to be reduced. The SHW scenario does not support peak load reduction on the Ruatoria feeder, because solar energy is stored as hot water to substitute electrical heating of water cylinder at night. There is a poor correlation between the profile for night-rate water heating and the Ruatoria peak load reduction required in the middle of the day. SHW replaces night-rate water heating and does not offset the daily peak load.

Valuation of the 50%/50% DGN/RE Ratio Mix

A summary of the results obtained for the 50%/50% DGN/RE Ratio are shown in figures 23 to 26.

Line Upgrade Deferral Met By 50% Diesel Genset and 50% HEP

-$200,000

-$100,000

$0

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

$800,000

$900,000

$1,000,000

$1,100,000

$1,200,000

$1,300,000

$1,400,000

$1,500,000

$1,600,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20


Net

Pre

sen

t V

alu

e o

f N

et

An

nu

al

DE

Ben

efi

t

RE Non-Grid-Supporting Energy


RE Distribution Loss


RE Grid-Supporting Energy

Gen Trans. Saving

RE Trans. Saving


RE Upgrade Deferral

Figure 23: 50%/50% DGN-HEP Analysis

In each scenario, the NPV of the net annual DE benefit remains constant, because the capacity and energy requirement that has to be met by DE for line upgrade deferral to take place has been defined as the same for all scenarios. However, as can been seen from figures 23 to 26, the contribution to the net benefit varies, based upon the year and the RE-DGN mix selected. The only exception to this rule, is provided by the non grid-supporting RE contributions, as these are surplus to requirement for line upgrade deferral, and do not cost anymore to produce – unlike diesel fuel which is only used to meet RE capacity-support shortfalls for line upgrade deferral. HEP provides the most additional non grid-supporting energy (figure 23), followed by WTG (figure 24), then SHW (figure 26) and finally PV (figure 25). The reason why PV provides so little non grid-supporting energy, is because most of the energy produced by PV is actually grid-supporting: the PV supply profile closely matches the Ruatoria demand profile and the periods when peak load reduction is required. The break down of components contributing to the Net Present Value of the diesel fuel and renewable energy mix in figures 23 to 26 is as follows: NPV of DE benefits [DGN+RE] = [DGN+RE] line upgrade deferral providing capacity-support, plus [DGN+RE] grid-supporting energy corresponding to line



upgrade deferral capacity-support periods, plus [RE] non-grid-supporting energy produced outside line upgrade deferral capacity-support periods, plus [DGN+RE] transmission saving from GXP peak load reduction from capacity-support, minus [DGN+RE] distribution losses in revenue to the lines company, from less energy distributed by the lines company to the end-user from the GXP, because the energy is supplied locally by distributed generation [DGN+RE] instead.

Line Upgrade Deferral Met By 50% Genset and 50% WTG DE

-$200,000

-$100,000

$0

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

$800,000

$900,000

$1,000,000

$1,100,000

$1,200,000

$1,300,000

$1,400,000

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$1,600,000

$1,700,000

$1,800,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20


Net

Pre

sen

t V

alu

e o

f N

et

An

nu

al

DE

Ben

efi

t






Gen Trans. Saving

RE Trans. Saving


RE Upgrade Deferral

Figure 24: 50%/50% DGN-WTG Analysis

Line Upgrade Deferral Met By 50% Diesel Genset and 50% PV

-$200,000

-$100,000

$0

$100,000

$200,000

$300,000

$400,000

$500,000

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$800,000

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$1,000,000

$1,100,000

$1,200,000

$1,300,000

$1,400,000

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Pre

sen

t V

alu

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f N

et

An

nu

al

DE

Ben

efi

t






Gen Trans. Saving

RE Trans. Saving


RE Upgrade Deferral

Figure 25: 50%/50% DGN-PVS Analysis



Line Upgrade Deferral Met By 50% Diesel Genset and 50% SHW

-$200,000

-$100,000

$0

$100,000

$200,000

$300,000

$400,000

$500,000

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$700,000

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$1,100,000

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DE

Ben

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t






Gen Trans. Saving

RE Trans. Saving


RE Upgrade Deferral

Figure 26: 50%/50% DGN-SHW Analysis

To summarize, the analysis shows several interesting features and trends:

• High non grid-supporting RE from HEP (figure 19) in early years; • Absence of non grid-supporting energy from PV (fig 21) and a poor return due to high capital costs; • Low overall grid-support from SHW (figure 22) due to mismatch between SHW off-peak power

storage (substituting electrical night-rate water heating) and the peak daily Ruatoria load.

The Influence of Carbon Tax and Fuel Costs on Diesel Price The base case selected for DGN operation assumed an annual increase of 2% per year in the price of diesel, with a starting price of: $1.00 / litre. More dramatic (exaggerated) fuel price increases of: 5 and 10% per year are included to evaluate the impact of scarcity of fuel at some future date, and / or the gradual introduction of carbon pricing. Initial fuel starting prices of $1.50 and $2.00 per litre are also considered to account for an abrupt change. These fuel pricing scenarios are included to compare the impact of substantial fuel price increases on the overall profitability of the various RE-DGN scenarios investigated. The influence of increasing fuel prices on the annual ROI of the different RE-DGN system combinations is compared in figures 27 to 30 below. Negative annual ROIs occur when the diesel fuel price becomes prohibitively expensive, and fuel costs over-ride the benefits provided by other factors. Figures 27 to 30 show the influence of fuel price on increasing the percentage of DGN in the total RE-DGN mix from 20% to 100%. Figures 27 and 28 show that a diesel price is reached when it is no longer profitable to increase the diesel component in the RE-DGN system. In figures 27 and 28, the optimum DGN percentage shifts from 100 to 80% once the base line diesel price and / or annual diesel price increase reaches a certain value. For a diesel price of $1.00/litre, this value is given by an annual increase of 10% in price; for a diesel price of $1.50/litre, this value is given by an annual increase of 5% in price; and, for a diesel price of $2.00/litre, this value is given by an annual increase



of 2% in price. In other words, as the base line price increases, the annual increase in price allowed diminishes. In figure 29, no optimum is reached with the PVS-DGN system, simply because the profitability of the system is heavily dependent on the DGN component (more so than for the other RE systems) – see figure 14 for a comparison. Figure 27: Influence of increasing fuel prices on the annual ROI of HEP-DGN systems

Figure 28: Influence of increasing fuel prices on the annual ROI of WTG-DGN systems

Figure 30 also shows that a diesel price is reached when it is no longer profitable to increase the diesel component in the RE-DGN system. The optimum DGN percentage shifts from 100 to 80% once the base line diesel price and / or annual diesel price increase reaches a certain value. For a diesel price of $1.50/litre, this value is given by an annual increase of 10% in price; and also, for a diesel price of $2.00/litre, this value is given by an annual increase of 10% in price.

Influence of Hydro on Rising Diesel Prices

-2%

0%

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8%

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20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage of Capacity Supplied by Diesel

Annual R

etu

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n Investm

ent (R

OI)

Hydro ($1.00@2%/yr)

Hydro ($1.50@2%/yr)

Hydro ($2.00@2%/yr)

Hydro ($1.00@5%/yr)

Hydro ($1.50@5%/yr)

Hydro ($2.00@5%/yr)

Hydro ($1.00@10%/yr)

Hydro ($1.50@10%/yr)

Hydro ($2.00@10%/yr)

Optimum ROI for $1.00 & 2%/yr inc. $1.50 & 2%/yr inc. $1.00 & 5%/yr inc.

Optimum ROI for $2.00 & 2%/yr inc. $1.50 & 5%/yr inc. $2.00 & 5%/yr inc. $1.00 & 10%/yr inc. $1.50 & 10%/yr inc. $2.00 & 10%/yr inc.

Influence of Hydro on Rising Diesel Prices

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20% 30% 40% 50% 60% 70% 80% 90% 100%


Annual R

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OI)

Hydro ($1.00@2%/yr)

Hydro ($1.50@2%/yr)

Hydro ($2.00@2%/yr)

Hydro ($1.00@5%/yr)

Hydro ($1.50@5%/yr)

Hydro ($2.00@5%/yr)

Hydro ($1.00@10%/yr)

Hydro ($1.50@10%/yr)

Hydro ($2.00@10%/yr)



Influence of Wind on Rising Diesel Prices

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OI)

Wind ($1.00@2%/yr)

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Wind ($1.50@5%/yr)

Wind ($2.00@5%/yr)

Wind ($1.00@10%/yr)

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Wind ($2.00@10%/yr)



Influence of Wind on Rising Diesel Prices

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20% 30% 40% 50% 60% 70% 80% 90% 100%


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Wind ($1.00@2%/yr)

Wind ($1.50@2%/yr)

Wind ($2.00@2%/yr)

Wind ($1.00@5%/yr)

Wind ($1.50@5%/yr)

Wind ($2.00@5%/yr)

Wind ($1.00@10%/yr)

Wind ($1.50@10%/yr)

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Not that the above trends are based on varying only fuel prices. It can be expected that if PV costs were progressively reduced over the 20 years, savings anticipated internationally would have the effect of pushing the middle of the PV curve (figure 29) upwards into a positive ROI. This analysis has not been carried out as it is beyond the scope of the present study. Figure 29: Influence of increasing fuel prices on the annual ROI of PVS-DGN systems

Figure 30: Influence of increasing fuel prices on the annual ROI of SHW-DGN systems

Summarizing Using ODRC asset valuation, this report presents two alternative methods for deriving the Net Present Value of capacity grid-support for distribution networks, using (a) capacity and (b) energy to calculate the benefit of line upgrade deferral from various distributed energy options. These results are

Influence of PV on Rising Diesel Prices

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OI)

PV ($1.00@2%/yr)

PV ($1.50@2%/yr)

PV ($2.00@2%/yr)

PV ($1.00@5%/yr)

PV ($1.50@5%/yr)

PV ($2.00@5%/yr)

PV ($1.00@10%/yr)

PV ($1.50@10%/yr)

PV ($2.00@10%/yr)

Optimum ROI for all scenarios

Influence of PV on Rising Diesel Prices

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20% 30% 40% 50% 60% 70% 80% 90% 100%


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OI)

PV ($1.00@2%/yr)

PV ($1.50@2%/yr)

PV ($2.00@2%/yr)

PV ($1.00@5%/yr)

PV ($1.50@5%/yr)

PV ($2.00@5%/yr)

PV ($1.00@10%/yr)

PV ($1.50@10%/yr)

PV ($2.00@10%/yr)

Optimum ROI for all scenarios

Influence of SHW on Rising Diesel Prices

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OI)

SHW ($1.00@2%/yr)

SHW ($1.50@2%/yr)

SHW ($2.00@2%/yr)

SHW ($1.00@5%/yr)

SHW ($1.50@5%/yr)

SHW ($2.00@5%/yr)

SHW ($1.00@10%/yr)

SHW ($1.50@10%/yr)

SHW ($2.00@10%/yr)

Optimum ROI for $1.50 & 10%/yr inc. $2.00 & 10%/yr inc.

Optimum ROI for $1.00 & 2%/yr inc. $1.50 & 2%/yr inc. $1.00 & 5%/yr inc. $2.00 & 2%/yr inc. $1.50 & 5%/yr inc. $2.00 & 5%/yr inc. $1.00 & 10%/yr inc.

Influence of SHW on Rising Diesel Prices

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0%

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20% 30% 40% 50% 60% 70% 80% 90% 100%


Annual R

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ent (R

OI)

SHW ($1.00@2%/yr)

SHW ($1.50@2%/yr)

SHW ($2.00@2%/yr)

SHW ($1.00@5%/yr)

SHW ($1.50@5%/yr)

SHW ($2.00@5%/yr)

SHW ($1.00@10%/yr)

SHW ($1.50@10%/yr)

SHW ($2.00@10%/yr)

Optimum ROI for $1.50 & 10%/yr inc. $2.00 & 10%/yr inc.

Optimum ROI for $1.00 & 2%/yr inc. $1.50 & 2%/yr inc. $1.00 & 5%/yr inc. $2.00 & 2%/yr inc. $1.50 & 5%/yr inc. $2.00 & 5%/yr inc. $1.00 & 10%/yr inc.



summarized below for the four DE combinations studied: 100%/0%, 80%/20%, 50%/50% and 20%/80% DGN/RE. Table 3: Capacity-based Line Upgrade Investment Deferral Methodology for Grid Supply-Support

%RE 0% RE (DGN-Only) 20% RE 50% RE 80% RE Capacity Max

MW $ Max

MW $ Max

MW $ Max

MW $

DGN+HEP 6.473 $739,051 2.2 $391,995 2.520 $470,418 2.202 $444,703 DGN+WTG 6.473 $739,051 1.242 $165,492 2.438 $281,188 2.916 $333,953 DGN+PV 6.473 $739,051 0.694 $124,050 1.649 $243,390 2.24 $307,870 DGN+SHW 6.473 $739,051 0.604 $25,623 0.805 $30,382 0.837 $31,212 The values in table 3 for capacity-based line upgrade deferral, show the maximum capacity-support provided (and the NPV associated with providing capacity-support over 20 years) from: (a) diesel genset by itself (0% RE); (b) the 20% RE component by itself; (c) the 50% RE component by itself; and, (d) the 80% RE component by itself. The balance of capacity required for scenarios (b) to (d), is provided by diesel, and is equivalent to the difference between what the diesel genset delivers by itself in scenario (a), and what the RE component of the total DE mix provides in scenarios (b) to (d). Table 4: Energy-based Line Upgrade Investment Deferral Methodology for Grid Support-Support

%RE 0% RE (DGN-Only) 20% RE 50% RE 80% RE Energy Total

MWh $ Total

MWh $ Total

MWh $ Total

MWh $

DGN+HEP 73,265.4 $739,063 30,987.3 $333,557 35,504.5 $382,461 31,604.5 $343,186 DGN+WTG 73,265.4 $739,063 16,223.2 $169,292 29,046.4 $295,473 34,287.5 $347,788 DGN+PV 73,265.4 $739,063 10,015.0 $108,746 21,682.3 $227,611 28,193.6 $292,370 DGN+SHW 73,265.4 $739,063 5,151.4 $44,758 6,240.1 $53,405 6,427.6 $54,924 The values in table 4 for energy-based line upgrade deferral, show the total energy-support provided (and the NPV associated with providing energy-support over 20 years) from: (a) diesel genset by itself (0% RE); (b) the 20% RE component by itself; (c) the 50% RE component by itself; and, (d) the 80% RE component by itself. The balance of energy required to meet the supply shortfall for scenarios (b) to (d), is provided by diesel, and is equivalent to the difference between what the diesel genset delivers by itself in scenario (a), and what the RE component of the total DE mix provides in scenarios (b) to (d).

Conclusions Future fuel price volatility and uncertainty with availability of supply and global warming taxation indicates a preference to at least combine diesel generation with a renewable component to minimize risk. Some scenarios, e.g. hydro and wind, indicate that the best annual ROI includes a 20-80% renewable energy component. This analysis demonstrates that the accumulated benefits of localized distributed energy (kWh) and capacity (kW) support exceed the costs for the case study developed for Eastland Networks’ Ruatoria Feeder in the East Coast region. The main analysis was based on a 10% demand growth rate to accentuate the effects, but lower growth rates exhibit similar trends. An investment strategy to replace line capacity upgrades with hybrid DE also offers a trade-off between direct ROI and intermittent renewable energy. Net benefits and costs will vary with differing stakeholder / user-operator perspectives. It all depends upon who is responsible for the investment and who benefits from the revenue streams generated. There are at least nine financial options



available for operating DE in New Zealand, depending on who the stakeholders are. The nine financial options (in no particular order) are:

1. standalone DE (where no grid is available, or to completely replace the existing grid); 2. DE consumer retail energy savings by reducing demand for grid electricity; 3. Customer-generator DE (wholesale) energy supply to an energy retailer; 4. DE grid-support for a downgraded network segment (e.g. single-phase feeder support for a

downgraded three-phase feeder); 5. DE grid-support to defer network expansion / upgrades; 6. DE wholesale energy spot price contributions; 7. DE Grid Exit Point (GXP) peak (transmission) demand reduction; 8. DE backup / UPS for high-risk power failure applications; and 9. DE reduction of distribution losses.

The real challenge however, is finding a way to concentrate the multiple stakeholder benefits for an option into a single revenue stream for a single stakeholder, so that the DE investment is cost-effective. This analysis shows that for load growth scenarios, distribution networks could contend for this position, and should seriously consider a DE investment encouragement strategy, in regions of high load growth, whether or not they are allowed ownership under market rules.

Moving Forward This research demonstrates quite clearly that there is an economic opportunity for distribution networks with capacity constraints and increasing customer demand to investigate DE line upgrade deferral. We encourage collaborative research and development amongst appropriate distribution networks with complimentary interests. Furthermore, we recommend that the Electricity Commission and Transpower work more closely with distribution networks and energy retailers to standardize such proceedings and establish industrial best practice. Finally, we believe that a regulatory framework should be developed which encourages a decentralized approach to infrastructure development. At present the regulatory and market structures support central generation. Much more detail is available from the analysis than has been presented in this report. Further implications could be drawn from the case study results or the methodologies could be easily applied to other case studies. In particular, the uptake of combinations of rooftop PV and storage systems in the urban and residential environment as an alternative to grid capacity growth could and should be investigated with urgency. The methodology applied is considered to be robust and thorough, and is based on ODRC (Optimized Depreciated Replacement Cost) data.

Acknowledgements This work has been completed with the financial support of the Foundation for Research, Science and Technology (FRST). Industrial Research is very grateful for the support provided by Eastland Networks Limited in producing this paper.

Line Upgrade Deferral Scenarios for Distributed Renewable Energy Resources

Technology

Transcript of Line Upgrade Deferral Scenarios for Distributed Renewable Energy Resources