A Multi-Criteria Evaluation of Wind Power in Montana

Transcription

1 A Multi-Criteria Evaluation of Wind Power in Montana Finding the top 5 incorporated Cities Mia Lieb-Lappen Middlebury College December 7, 2009 Word Count: 968

2 I. INDRODUCTION Montana has the 5 th highest wind power potential in the nation with the capability of generating 1,020 billion kwh per year. 1 Capitalizing on this clean source of power would relieve Montana s economic dependency on oil, coal and natural gas which currently accounts for 30% of its GDP. 2 Physical, social/economic, and visual factors all influence wind power development. These three criteria are analyzed in order to choose the five most suitable incorporated cities in Montana develop wind energy. Physical factors that influence suitability for wind turbines include wind power, terrain, land cover, and proximity to existing infrastructure. Ideally, wind turbines would exist in areas of high wind power, flat land, buildable land, and areas close to existing transmission lines. Social and economic factors include proximity of existing cities and land ownership. The former is important because people in cities need to be able to use the new green energy and if they are near the source, it will cost less. The later is of great significance because ownership of land affects the ease of development. Visual factors are also going to influence the ease of wind turbine development. Many projects underway today face resistance because people do not want to see them or listen to them, especially in their backyards. Thus, an analysis of visibility of the proposed wind turbines from the Lewis and Clark hiking trail, recreation sites, and towns will be considered. First, an understanding of Montana s landscape will be illustrated in order to understand the study area. Next, the method of performing a weighted multi-criteria evaluation (WMCE) of physical, social and economic, and visual criteria used to choose wind turbine sites will be explained. The results of the three initial MCEs will be aggregated into one larger MCE to yield overall suitability scores for all land in Montana. Then, the incorporated cities with the most suitable land in a 30 km radius will be chosen. Lastly, conclusions regarding the geography and composition of these cities and recommendations for further work will be offered. 1 American Wind Energy Association, 2 American Council for an Energy-Efficient Economy

3 II. STUDY AREA Montana is made up of complex network of power transmission lines which are almost at full capacity. However, future wind turbine energy could either connect to the current lines or simply be added to the current infrastructure via existing poles. Map 1: Transmission Lines and Incorporated Cities in Montana Map 2: Wind power in Watts per square meter in Montana. Source: True Wind Solutions

4 III. METHODS Multi-Criteria Evaluation A weighted multi-criteria evaluation (WMCE) was used in order to determine the most suitable areas for wind turbines. S = w i x i *Πc i In this evaluation, the suitability index, S (rated on a scale of 1-10), equals a linear combination of various criteria scores (x i ) multiplied by all of the constraints (Πc i ). The weights (w i ) give a relative importance of each criteria score. Suitability scores were based off of three types of criteria, physical, social and economic, and visual. Physical Criteria 1. WIND POWER Table 1: Wind power from Map 2 was classed by True Wind Solutions into the 7 classes in Table 2. These classifications were scaled to 10 by scaling proportionally by a factor of 10. Rating Wind Potential (W/m 2 ) Suitability Score (Scale to 7) Suitability Score (Scale to 10) Poor Marginal Fair Good Excellent Outstanding Superb Map 3: Wind Power Reclassified

5 2. TERRAIN Map 4: Terrain Based on Slope of Elevation Data Table 2: Suitability Scores of Slope Slope (percent rise) Suitability Score Map 5: Suitability of Terrain Based on Flatness: The suitability of terrain was determined based on the flatness of an area because flatter land would be easier to build on. This was determined by finding the slope from elevation data provided by the U.S. Geological Survey Center for Earth Resource Observation and Science. The pixel size of Maps 4 and 5 is 90m by 90m or 8100 square meters. This is over 2 acres and a 2MW wind turbine only requires 2/3 of an acre per turbine ( Thus, the flatness of one pixel of the map is adequate to place one wind turbines.

6 3. LAND COVER Map 6: Land Cover Data was attained from the National Land Cover Database for superzones 3, 4, and 6 ( Barren Land (Rock/Sand/Clay) --> 10 Cultivated Crops --> 8 Deciduous Forest --> 6 Developed --> 2 Emergent Herbaceous Wetlands --> 4 Evergreen Forest --> 6 Grassland/Herbaceous --> 10 Mixed Forest --> 6 Open Water --> 0 Pasture/Hay --> 8 Perennial Ice/Snow --> 4 Shrub/Scrub --> 10 Woody Wetlands --> 4 Map 7: Relative Suitability to Build on Land

7 4. DISTANCE TO INFRASTRUCTURE Map 8: Distance to Existing Transmission Line Distances from transmissions lines were calculated in order to define areas that would be easier to connect to the existing grid. These distances were reclassified according to Table 3, with closest distances receiving higher suitability scores. Table 3: Distance to Transmission Line Classifications Distance to Line (m) Suitability Score The Physical Criteria factors explained above were weighted by their relative importance in planning for wind turbines. The weights listed in Table 4 were used and multiplied to each suitability map. These weighed maps were then added in order to recreate an overall suitability index from 1 to 10. The lakes and rivers depicted in Map 3 were used as constraints and assigned suitability scores of 0. Table 4: Weights of Physical Criteria Criteria Weight Wind Power 0.5 Terrain 0.2 Land Cover 0.1 Distance to Lines 0.2

8 Map 9: Physical Suitability of Land in Montana for Wind Turbine Social and Economic Criteria 1. PROXIMITY TO CITIES Map 10: Incorporated cities were isolated from a map of all towns. Then, the distance from all areas in Montana to these incorporated towns was computed as seen in Map 10. These distances were then reclassified according to the same breaks as for distance to transmission lines (Table 5).

9 Table 3: Distance to Transmission Line Classifications Distance to City (m) Suitability Score LAND OWNERSHIP Map 11: Land Ownership: Certain types of land ownership, specifically wildlife refuge, wilderness, and national park areas cannot be built on according to Chris Rodgers 09 and therefore those areas will act as constraints and receive a suitability score of 0. Table 6: Ease of Development on various land Land Ownership Difficulty to Build Private Land 0 Federal Land 1 Recreation Sites 2 National Forests 3 Indian Reservations 4 State Parks 5 Wilderness Management 6

10 Map 12: Land ownership was reclassified according to suitability for development. Classes defined in Table 6. Land in multiple categories received the sum of the difficulty scores. Overall scores were rescaled to a scale of 1 to 10 with 10, the easiest to develop. Table 7: Weights of Social Criteria Criteria Weight Proximity to Cities 0.2 Land Ownership 0.8 Map 13: Suitability based on Social and Economic Factors with weights listed above and constraints of wilderness areas, national parks and wildlife refuge areas considered.

11 Visual Criteria To speed up this slow process, elevation data used in the Physical analysis was resampled into larger cell sizes. Then, an offset of 100 meters was applied to account for the height a windmill would be. Viewsheds reported the number of times a spot is viewed from each point or vertex on a line. These were then reclassified according to natural breaks in the data and scaled from 1 to LEWIS AND CLARK TRAIL Maps 14: View from the Lewis and Clark Trail Map 15: Suitability of View

12 2. RECREATION SITES Map 16: View from Recreation Sites Map 17: Suitability of View from Recreation Sites

13 3. TOWNS Map 18: View from Towns Map 19: Suitability of View from Towns Table 4: Weights of Visual Criteria: These weights were used to produce and overall visual suitability as seen in Map 20. Criteria Weight Lewis and Clark 0.3 Recreation Sites 0.4 Towns 0.3

14 Map 20: Visual Suitability of Land in Montana for Wind Turbine TOTAL MCE Table 8: Relative Weights for the Total MCE Criteria Weight Physical 0.5 Social/Economic 0.4 Visual 0.1 Map 21: Overall Suitability of Land for Wind Turbines

15 TOP 5 Evaluation Determining the five most suitable incorporated cities first required defining a 30 mile radius for each incorporated city. Also, from the suitability scores of the final WMCE, only areas with a score of 8 or higher were isolated. Then, all of the pixels considered high were summed for each incorporated area. The five highest scoring areas were isolated and identified. Map 21: Areas Included in Each Incorporated Area Map 22: Areas with a Score of 8 or Higher

16 Map 23: MCE of the Incorporated Cities: The sum of the suitability in each area Map 24: Top Five Incorporated Areas and the Existing Transmission Lines! Shelby! Havre! Fort Benton! Harlowton! Big Timber

17 RESULTS Multi-Criteria Evaluation The MCE of each section, Physical, Social and Economic, and Visual all yielded very different results. However, the overall MCE yielded the most suitable towns that fit all of the factors to some extent. This extent should be related to the proportion of each factor in the overall MCE (see overall weights in Table 9 below). Importantly, as shown in Map 23, the high suitability areas were clustered which is crucial in order to build a large wind farm. Several examples follow of how the top cities offer very suitable locations for these wind farms. Table 9: Criteria Major Weight Factor Minor Weight Overall Weight Physical 0.5 Wind Power Terrain Land Cover Distance to Lines Social/Economic 0.4 Proximity to Cities Land Ownership Visual 0.1 Lewis and Clark Recreation Sites Towns Physical Examples: Map 25: The top 5 cities are in fact on low sloped, flat areas

18 Map 26: Top 5 cities are in the windiest areas: This makes sense considering overall, the Wind potential was given the highest overall weight of 0.25 (see Table 9) Social and Economic Examples: Map 30: Top 5 cities were all in private land (starts represent five cities chosen).

19 Visual Examples Map 31: Top 5 cities are not visible from many points along the Lewis and Clark Trail V. CONCLUSION Overall, this large WMCE managed to chose 5 very appropriate cities to build wind turbines, Big Timber, Harlotown, Shelby, Fort Benton, and Havre. However, as shown in Table 9, some factors had minimal influence on the locations chosen. Moreover, all classifications were partly arbitrary and reflect subjective views of relative importance. There are several sources for error in this analysis that could be mitigated upon further investigation. For example, all of the data used was on various scales and based on various interpolations. Also, error from the resampling of elevation data add to the uncertainly of the results. There were also many factors such as income distribution that would influence the placement of wind turbines. With more time this analysis could be possible. Thus, future work would first involve a more extensive analysis of even more criteria. Also, more research can be done to explore the proper classifications to define the ease of development on different land types with different owners. Next, future work would involve going into the field and analyzing the grounds and negotiation with land owners. Once exact locations are chose, a least cost path of connecting to existing infrastructure could be performed. Overall, this method of a series of weighted multi-criteria evaluations proved effective in suggesting appropriate locations for wind turbines.