Site suitability report for a wind farm in the UK

Site suitability report for a wind farm in the UK

Gonzalo Romero

16/03/2012

GEOG5060 Gonzalo Romero

INDEX

1. INTRODUCTION.....................................................................................................3

2. PHASE 1...................................................................................................................3

2.1. Input data......................................................................................................................3

2.2. Selection of criteria.......................................................................................................4

2.3. Initial modelling assessment.........................................................................................5

3. PHASE 2...................................................................................................................9

3.1. Input data......................................................................................................................9

3.2. Selection and analysis of criteria................................................................................103.2.1. Environmental criteria.........................................................................................................113.2.2. Social criteria.......................................................................................................................113.2.3. Economic criteria.................................................................................................................123.2.4. Technical criteria.................................................................................................................12

3.3. Weighing of criteria....................................................................................................12

3.4. Site selection...............................................................................................................13

4. DATA QUALITY...................................................................................................17

2


1. INTRODUCTION.

This report focuses on the site selection phase of a 90MW wind farm in Britain.

Selection of suitable areas to build a wind farm requires a set of considerations that

range from technical to environmental factors. Such considerations are mainly based on

the “Best Practice Guidelines for Wind Energy Development” (BWEA, 1994). Potential

sites for wind farms are identified using a Multi-Criteria Evaluation (MCE) & GIS

approach. The project is carried out under 2 different phases. First phase aims to search

for potential sites using key criteria to do initial modelling. Second phase is developed

on the previous selected sites adding new technical and environmental criteria. Main

aspects mentioned in this report are data source, data quality, weighting criteria and

selected method used to reach the final decision.

2. PHASE 1.

1.1. Input data.

Next table shows initial data used in this project.

SourceFile

FormatDescription Spatial Reference System

BWEA .asc 1 km2 wind speed data from at 10, 25 and 45m above ground level

British National Grid

CIS2000 .asc 1 km2 Digital Terrain Model (DTM) British National GridCIS2000 .asc 1 km2 Dominant Land Cover (DLC) British National GridDigimap .shp county_region 1:50,000 scale British National GridTable 1. Data used in phase 1.

As stated in table 1, some data have unknown spatial reference system (SRS). After

converting ASC files into GRID format it is observed that such layers do not match

when are added into ArcMap. This problem is fixed by opening layer properties using

ArcCatalog. British National Grid is selected as SRS, and linear unit is changed from

meters to kilometer. Finally the visible extent properties (left and bottom) are also

changed for “DTM” and “wspeed” layers.

3


Figure 1. Input data for phase 1. Source: ArcMap 10.

1.2. Selection of criteria.

Criteria are mainly related to technical factors as wind speed (orientation) or

topographic site conditions (slope, elevation), and environmental factors as soil type.

Their importance is mentioned briefly.

4


1) Orientation: dominant wind direction is a crucial technical factor for a wind

farm.

2) Slope: slope poses a problem of limitations to site access. It must be considered

that during the construction phase moderate or strong slopes are not appropriate

for heavy goods vehicles (BWEA, 1994). On the other hand, faster wind occurs

more often when there is strong variation in threshold slope (EDINA, 2001).

3) Land type: suitability to locate a wind farm varies depending on the land type.

4) Wind speed: probably the most evident technical factor. A wind farm is not

feasible if there is not a certain minimum annual average speed.

1.3. Initial modelling assessment.

Correspondent GRIDs are reclassified according to Boolean criteria where 1 (total

constraint) is not suitable and 0 (no constraint) is suitable.

1) Orientation

“Aspect” layer is derived from “DTM” layer using Spatial Analyst Tools

(Surface_Aspect). According to information from Exmoor National Park, the most

common winds are south-westerlies. This means that our potential sites will have a

westerly orientation.

AspectOld value New valueFlat 0North 1Northeast 1East 1Southeast 1South 1Southwest 0West 0Northwest 0

Table 2. Aspect reclassification.

2) Slope

“Slope” layer is derived from “DTM” layer using Spatial Analyst Tools

(Surface_Slope). Z factor was modified as x,y units and z units are not in the same units

of measure. The problem of slope is that has been derived from a DEM where its spatial

resolution is 1 km. This leads to inaccuracy that must be taken into account during the

analysis. Layer is reclassified considering slope not to be greater than 10% (Baban,

2001).

5


SlopeOld value New value0-10% 0>10% 1

Table 3. Slope reclassification.

3) Land type

Dominant land cover is reclassified according to table 4.

Code Class Value1 Broad-leaved / mixed woodland 12 Coniferous Woodland 13 Arable and Horticultural 04 Improved Grassland 05 Semi-natural / rough grass and bracken 06 Montane, Heath and Bog, and inland rock 07 Built-up and Gardens 18 Standing open water and canals, rivers and

streams1

9 Coastal 010 Sea/Estuary and Unclassified 1

Table 4. Land characteristics. Source: Land Cover Map of Great Britain (2000).

4) Wind speed

Although we have layers containing wind speed data from BWEA at 10, 25 and 45m

above ground level, we finally use wind speed data at 45m as hub heights are 45m

above ground level (Siemens, 2012). Such layer is reclassified considering wind speed

should be greater than 6,5m/s to have a wind resource suitable for wind development

(US Department of Energy, 2012)

Wind SpeedOld value New value

>6.5 0<6.5 1

Table 5. Wind speed reclassification.

Sieve Map

The initial map with potential sites is based on Boolean Criteria as it helps to

differentiate areas that are completely unsuitable for a wind farm.

The output “Sieve” layer is the result of using CellStatistics tool in Spatial Analyst.

“Maximum” operator is used to determine the maximum (largest value) of the inputs for

each cell. Maximum operator ensures the “area will be suitable to the extent of its best

quality” (Jiang p. 178, 2000). Hence values equal to 0 are selected for phase 2. All the

analysis process can be observed in Figure 2.

6


Figure 3 shows the location of the selected area where there is an important number of

potential sites. Phase 2 is carried out in this selected area where potential sites occupy a

total extent of 2.428 km2.

Figure 2. Flow chart for phase 1. Source: Model Builder.

7


Figure 3. Potential sites for a wind farm in UK. Source: ArcMap 10.

8


3. PHASE 2.

1.4. Input data.

In this second phase more constraint factors are added. Table 6 shows the additional

input data used in this second phase. Such inputs are shown graphically in figure 4.

SourceFile

FormatDescription Spatial Reference System

Digimap .shp Motorways 1:50,000 scale British National GridDigimap .shp A_roads 1:50,000 scale British National GridDigimap .shp Urban_Region_South 1:250,000 British National Grid

Natural England

.shp

Special Conservation Areas of England (areas which have been identified as best representing the range and variety within the European Union of habitats and (non-bird) species listed on Annexes I and II to the EC Habitats Directive). 1:10,000 scale


Natural England

.shpSite of Special Scientific Interest (SSSI). 1:10,000 scale


Natural England

.shp National Parks. 1:10,000 scale British National Grid

Digimap .shp Woodland region 1:50,000 scale British National GridDigimap .shp Rivers. 1:50,000 scale British National GridNational Grid

.shp Lines (electricity network) British National Grid

Table 6. Additional data used in phase 2.

9


Figure 4. Input data for phase 2. Source: ArcMap 10.

1.5. Selection and analysis of criteria.

Multi-Criteria Evaluation used for this second phase, involves environmental, social,

economic and technical considerations (Baban, 2001) for a better assessment of

potentiality, limitations and constraints of a potential wind farm site. Analytic Hierarchy

10


Process (AHP) is used “to make a decision in an organized way, generate priorities and

establish the relative importance of the criteria” (Saaty p.85, 2008).

Goal Objectives Attributes

Ecological Area (SCA, SSSI, National Parks) Environmental

Rivers

Social Urban areasSuitability

Road networkEconomic

Electrical network

Technical Woodlands

Figure 5. Hierarchical organization of the criteria.

Prior the analysis start, several environment options were set in the Geoprocessing

toolbar as workspace, cartography (British_National_Grid) and mask in Raster Analysis

(2 areas selected in phase 1).

1.5.1. Environmental criteria.

There are environmental restrictions due to ecological characteristics of some areas. In

this respect no sites are selected within the boundaries of Special Conservation Areas

(SCA) as well as Sites of Special Scientific Interest (SSSI’s) and National Parks

(EDINA, 2001). Analysis is carried out in ArcMap using the tool “Merge” to combine

the different layers. The output “EA” (ecological area) is converted into raster and

reclassified giving highest values (10) to cells included in ecological areas and lowest

value (0) to the rest of cells.

On the other hand, to avoid water pollution, potential sites cannot be located within 200

meters from rivers (EDINA, 2001). Buffer zones are created for “rivers” layer, and the

output is converted into raster. As previous paragraph, we obtain a raster which is

reclassified giving highest value (10) to cells included in such areas and lowest value (0)

to the rest of cells.

1.5.2. Social criteria.

Due to noise pollution, it is considered potential sites cannot be located within 500

meters from urban areas or single dwellings (EDINA, 2001). Same analysis as for rivers

11


is applied. Cells included within 500 meters from such areas are giving the highest

value (10) whereas the lowest value (0) is given to the rest of cells.

1.5.3. Economic criteria.

It is evident that the further away potential sites are from road network the more

expensive the project will be. This is also valid for distance from electrical network. In

this sense, potential sites cannot be located further than 10 Km from roads and electrical

network (Baban, 2001).

As there are 2 road layers for roads, Merge tool is used to convert them into one single

layer. Once it is converted into raster, Cost distance from roads is obtained using slope

as input cost raster. Finally the output raster is reclassified according to table 7. As for

electrical network, similar analysis is undertaken.

Euclidian distance from Road Network

Euclidian distance from Electrical Network

Old value New value Old value New value<1000 meters 0 <1000 meters 02000 meters 1 2000 meters 13000 meters 2 3000 meters 24000 meters 3 4000 meters 35000 meters 4 5000 meters 46000 meters 5 6000 meters 57000 meters 6 7000 meters 68000 meters 7 8000 meters 7 9000 meters 8 9000 meters 810000 meters 9 10000 meters 9>10000 meters

10 >10000 meters

10

Table 7. Euclidian distance reclassification.

1.5.4. Technical criteria.

To avoid possible interference from woodlands it is consider a buffer of 250 meters.

Same analysis as for urban areas and rivers is applied. Cells included within 250 meters

from woodlands are giving the highest value (10) whereas the lowest value (0) is given

to the rest of cells.

1.6. Weighing of criteria

As AHP is used, all criteria were weighted using pair wise comparison method (see

Table 8).

Intensity of importance Definition Explanation

1 Equal ImportanceTwo activities contribute equally to the objective

12


2 Weak or slight

3 Moderate importanceExperience and judgment slightly favor one activity over another

4 Moderate plus

5 Strong importanceExperience and judgment strongly favor one activity over another

6 Strong plus

7Very strong or demonstrated importance

An activity is favored very strongly over another; its dominance demonstrated in practice

8 Very,very strong

9 Extreme importanceThe evidence favoring one activity over anotheris of the highest possible order of affirmation

Table 8. Fundamental Scale used in Pairwise Comparison (Saaty p.85, 2008).

Table 9 “indicates how many times more important or dominant one element is over

another element with respect to the criterion or property with respect to which they are

compared” (Saaty p. 85, 2008).

Ecological Area

Rivers Urban areas

Road Network

Electrical Network

Woodlands

Ecological Area 1 2 1/2 3 3 4Rivers 1/2 1 1/3 1/2 1/2 2

Urban areas 2 3 1 2 2 6Road Network 1/3 2 1/2 1 1 4

Electrical Network 1/3 2 1/2 1 1 4

Woodlands 1/4 1/2 1/6 1/4 1/4 1

Table 9. Criteria weights using AHP.

According to Table 9 relative importance is obtained for each factor:

Ecological Area 0,19Rivers 0,10Urban areas 0,29Road Network 0,19Electrical Network 0,19Woodlands 0,05

Table 10. Relative importance of factors.

1.7. Site selection.

In order to choose the most suitable site, Map Algebra tool was used to obtain a final

raster derived from the different relative importance of each criterion. The output values

range from 0 (no constraint) to 10.1 (maximum constraint). Finally the output of the

MCE is reclassified into 7 classes of suitability (Table 11).

13


Old Values New Values Definition0-1 1 Land with very minor or no limitations to use1- 2.5 2 Land with minor limitations2.5 - 3.5 3 Land with moderate limitations3.5 - 4.5 4 Land with moderately severe limitations4.5 – 5.5 5 Land with severe limitations5.5 – 7 6 Land with very severe limitations7 – 10.1 7 Land with extremely severe limitationsTable 11. Land suitability reclassification.

All the analysis carried out to obtain the most suitable locations for a wind farm, can be

seen in figure 6.

Figure 6. Flow chart for phase 2. Source: Model Builder.

14


Figure 7. Land Suitability Map for a wind farm in UK. Source: ArcMap 10.

The next step is to overlay the potential sites for wind farms selected in phase 1.

15

Selected site


Figure 8. Selected site. Source: ArcMap 10.

Potential sites have to take account of the size of a 90MW wind farm. According to

Siemens Corporation (2012), a wind turbine of 3.6MW has a swept area of 9000 m 2.

Hence to build the require wind farm, we need 25 wind turbines and 225000 m2 of land.

The selected site (see figure 8) occupies plenty of space as has a total extent of 9 km2

and is located in land with very minor or no limitations to use.

Finally, in order to ensure slope of selected site is less than 10%, DEM of 50 meters

resolution was downloaded for that area from Digimap (see figure 9).

Figure 9. Selected site. Source: ArcMap 10

16

Selected site

Selected site

Selected site


It can be observed that slope of selected site is less than 10%, using a DEM of 50m resolution.

4. CONCLUSION.

The site selected for a wind farm is based on MCE. Phase 1 uses Boolean Criteria as

there are clear thresholds that determine if a project with these characteristics can be

carried out or not. Such constraints defined by specific thresholds, can be classified as 0

(no constraint) or 1 (total constraint). However in phase 2 there are not only constraints

but also fuzzy sets. The inclusion of factors in our analysis yields a different procedure

known as Weighted Linear Combination (Jiang et al, 2000). In this sense economic

factors (cost distance from roads and electrical network) represent a continuous degree

that range in our analysis from 0 (most suitable) to 10 (less suitable). Fuzzy methods

have proven to be more useful than Boolean methods for classification of continuous

variation (Burrough, 1992). On the other hand, it is more difficult to estimate

uncertainty because of the use of criteria of weighted linear combination, as

uncertainties are combined through an averaging process (Jiang et al, 2000). In this

respect, DEM should be of the highest quality as a lack of accuracy in it will propagate

throughout the analysis (Haklay, 1998).

17


REFERENCES

Baban, S., Parry T. (2001). Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renewable Energy 24, 59–71.

Burrough, P. A., Macmillan R. A. & Deursen, W (1992). Fuzzy classification methods for determining land suitability from soil profile observations and topography. Department of Physical Geography, University of Utrecht, The Netherlands and Alberta Research Council, Edmonton, Alberta, Canada

Case Study: Modelling Site Suitability for Wind Farms (2001). EDINA (University of Edinburgh). [Accessed 03 March 2012]. Available from: http://edina.ac.uk/learning/emapscholar/casestudies/foley/Manual.pdf

Haklay, M and Feitelson, E and Doytsher, Y (1998). The potential of a GIS-based scoping system: An Israeli proposal and case study. Environmental Impact Assessment Review , 18 (5) 439 - 459.

Jiang, H., Eastman J. R. (2000). Application of fuzzy measures in multi-criteria evaluation in GIS. Int. J. Geographical Information Science, vol. 14, no. 2, 173± 184.

Saaty, T.L., (2008). Decision making with the Analytic Hierarchy Process. Katz Graduate School of Bussiness, University of Pittsburgh, USA.

Wind Turbines (2012). Siemens. [Accessed 03 March 2012]. Available from: http://www.energy.siemens.com/hq/en/power-generation/renewables/wind-power/wind-turbines/swt-3-6-107.htm#content=Technical%20Specification

Wind Powering America (2012). US Department of Energy. [Accessed 03 March 2012]. Available from: http://www.windpoweringamerica.gov/wind_maps.asp

18

http://www.windpoweringamerica.gov/wind_maps.asp

http://www.energy.siemens.com/hq/en/power-generation/renewables/wind-power/wind-turbines/swt-3-6-107.htm#content=Technical%20Specification

http://www.energy.siemens.com/hq/en/power-generation/renewables/wind-power/wind-turbines/swt-3-6-107.htm#content=Technical%20Specification

http://edina.ac.uk/learning/emapscholar/casestudies/foley/Manual.pdf

Site suitability report for a wind farm in the UK

Documents

Transcript of Site suitability report for a wind farm in the UK