Big Sky, Big Wind. Wind Power Development in Montana. Marty Schnure GG320: GIS December 7, 2009 Word count: 908

Transcription

1 Big Sky, Big Wind Wind Power Development in Montana Marty Schnure GG320: GIS December 7, 2009 Word count: 908

2 Introduction Historically, Montana's energy has come primarily from coal and hydroelectric power. More recently, as climate change and the perils of dependence on fossil fuels have entered the public consciousness, the state's extraordinary wind power potential has drawn a great deal of interest. However, the limiting factor in Montana's transition to wind power is not suitable land for wind farms, but rather the transmission network to link supply to demand, wind sites to population centers. As wind farms have begun to spring up across the state, the existing electrical transmission network has begun to approach full capacity, with little room to accommodate new loads. Consequently, Montana's transition to a low-carbon economy requires not just selecting new sites for wind power production, but also constructing new transmission lines to connect these sites with consumers. This study seeks to identify and evaluate suitable sites for new wind farms in Montana that can be linked with new transmission lines to nearby cities. To do this, I focus on four kinds of criteria: 1) physical constraints, such as attractive wind conditions and favorable terrain, 2) social constraints, such as protected lands, 3) preferences of proximity, such nearness to roads and cities, and 4) adequate land area to achieve economies of scale. Based on this evaluation, I have identified the five incorporated cities most able to incorporate wind power into their energy portfolios. In this report I will first describe the methods I used to evaluate site suitability, including social constraints, physical constraints, and proximity preferences. I will then discuss my results and potential elements of opposition to the new wind projects. I will conclude by discussing the limitations of this analysis, as well as recommendations for a course of action and further study. Cut Bank Chinook Harlem Missoula ^Helena Great Falls Harlowton Bozeman Billings Montana's wind Top 5 cities for wind power Major cities Montana Wind Stats (as of 12/2008) Total installed wind energy capacity (MW): Current wind energy capacity under construction (MW): 0 Total wind energy potential (Billions of kwh/year): 1,020 Average potential power output (MW): 116,000 Ranks 5 th in the U.S. for potential wind energy production Ranks 18 th in the U.S. for current wind energy production Montana Wind Stats, National Wind, Still Blustery

3 Physical constraints: Wind, Land cover, Slope

4 Social constraints One of the greatest constraints on selecting sites for both wind turbines and transmission lines are those of land ownership. In this case, I considered different types of designated lands and excluded those that are protected or otherwise restricted against development. These restricted lands include state parks, coincidental priority conservation areas, certain federal lands (Department of Defense land, designated wilderness), National Forests, Bureau of Land Management Special lands, wilderness, wildlife refuges, wildlife management areas, and National Parks. I "erased" each of these lands from the rest of the state of Montana in order to exclude it from the analysis of suitable lands for wind farms and transmission lines. Total restricted lands Restricted land Non-restricted land State Parks Coincidental priority conservation areas Federal lands National Forests BLM Special Wilderness Wildlife Refuges Wildlife Management Areas National Parks

5 Preferences of proximity: Roads, Cities, Existing transmission lines Proximity to roads Near Far Both wind farms and transmission lines must be accessible by road in order to facilitate construction, maintenance, and monitoring. Since it is expensive and destructive to build new roads, it is preferable to select sites that are near to existing roads. In this analysis, I did not decide that any particular distance was too far. Instead, I simply divided the distances into ten classes and prioritized them on a 1-10 scale, where the nearest sites were optimal and the most distant sites were least optimal. I treated highways, secondary roads, and local roads equally; highways are fastest, but it may be local roads that are most likely to lead to the best sites for wind. Proximity to existing transmission lines Near Far Deciding how to incorporate existing transmission lines into this analysis was the most difficult and uncertain element of this study. The problem at hand is that Montana's existing transmission network is nearly maxed out and new transmission lines need to be built, but not all existing lines are maxed out, and I did not have any information about the capacity of each line or the current loads. However, regardless of whether or not an existing line is maxed out, it may be optimal to build new lines parallel to the existing lines simply because the existing lines are already accessible by road, reducing both start-up and maintenance costs. For this analysis, I decided to prioritize being near to existing transmission lines, but give it no more weight than proximity to roads. As with roads, I classified the distances from existing lines into ten classes and weighted them accordingly. Proximity to incorporated cities 30 city buffer Since energy is lost in transmission due to resistance and transmission lines cost money to build and maintain, it is ideal to select wind farm sites that are in close proximity to population centers, in this case incorporated cities. I decided that 30 kilometers was a reasonable cutoff distance from city centers for wind sites, since it appeared that plenty of suitable land existed within that distance. I created a 30 kilometer buffer around each incorporated city and excluded all lands outside of those buffers. This way, building transmission lines will be less expensive, less energy will be lost in transmission, and maintenance costs will be lower because the sites are close.

6 Suitability Result Suitability classes, only large areas 1. Big Timber Incorporated cities City buffer Unsuitable Sufficient Good Optimal 2. Chinook 3. Harlowton Suitability classes, all areas Information about turbine spacing from Power Naturally, "Wind Power Project Site: Identification and Land Requirements." After the restricted and unsuitable areas were all excluded and the weighted criteria for wind classes, slope, landcover, and proximity to roads, cities, and existing transmission lines were all taken into account, the final product was a map of Montana with three classes of suitable lands: sufficient, good, and optimal. From there, I made an exclusion based on the size of the contiguous suitable zones. Treating all three classes of sites equally, I calculated the area of each group of contiguous suitable lands and eliminated all those groups less than 562,500 square meters in area. This distinction is based on the notion that in order for a wind farm to experience economies of scale, it should generate at least 30 MW of power. Since we are working with 2 MW turbines, this means that each wind farm needs to have a minimum of 15 turbines. How much land do 15 turbines need? There is a tradeoff here: land is money, so the turbines should be placed as close together as possible; however, a turbine downwind from another turbine experiences interference called the "wake effect", which induces energy losses and can cause damage to the turbine, requiring extra maintenance. The objective, then, is to optimize the balance between wake effects and costs. Based on a rotor diameter of 92 meters, I estimated that rows needed to be spaced 500m apart and turbines within rows could be spaced 300m apart, for a total of 37,500 square meters per turbine and 562,500 square meters for all fifteen. By excluding all areas smaller than this, I effectively excluded all areas that would not achieve economies of scale. I then idenfitied the top five cities based on the total amounts of sufficient, good, and optimal land each city had within 30, with optimal being the most valuable. 4. Cut Bank 5. Harlem

7 Connecting wind sites to cities: Siting transmission lines Big Timber Chinook Using the land constraints and weighted preferences for transmission lines, I calculated a possible path for a transmission line to connect a potential wind site to each city center. The only criteria I changed from the turbine site criteria is that transmission lines can be built through forests (sufficient) and that they can be built on developed land. If I were to have excluded developed land, all roads would have been excluded, and it is along roads that ransmission lines likely ought to be built. This type of analysis is extremely limited, so these paths are not necessarily the most efficient of all possible paths, but they are feasible and are meant primarily for visualization purposes. Harlem Cut Bank Harlowton City center Water bodies Existing transmission lines Local roads Secondary roads Highways Suitable wind power zones Potential wind power site Possible path for new transmission line 0 10

8 Potential sources of opposition Visual impacts to recreational sites Harlowton Visual impacts to cities Big Timber Chinook Selected cities BLM recreation sites Visible from LCT Visible from several rec sites Cut Bank Harlem Wind turbines at a large portion of the sites may be visible from the city center. I did not include this in my site suitability analysis, partly because I believe that people should see where their energy comes from. Visible from city 0 10 Lewis & Clark Trail Potential wind power sites Population density by county One common source of opposition comes from those who are concerned about the implications of being able to see the wind turbines from recreational areas and historic sites such as the Bureau of Land Management's recreation sites and the Lewis and Clark Trail. I did not include this in my analysis for two reasons. First, since part of the purpose of wind turbines is to promote a cleaner environment and protection of wild lands, it is unlikely that recreators who are enjoying those areas would outwardly oppose seeing them. Second, the method of analysis used here is flawed and the results ought to be taken lightly. The analysis assumes a barren landscape; that is, one without trees or buildings to block views. It also does not take into account the limits of the human eye; for example, a wind turbine many kilometers away might still be theoretically visible in that nothing is blocking the view, but it will appear so small that it would hardly be noticable. For these reasons, the areas identified here do not represent the true areas which can be seen from the BLM recreation sites and the Lewis and Clark Trail. Many wind power development projects in the past, such as the Cape Wind project, have been ultimately halted due to opposition from citizens who believe that the large wind turbines will mar their view of the landscape or even drive their property values down. The majority of sites we have identified here are located in areas of low-medium population density, which suggests that fewer people will be directly affected by the construction of wind farms. In areas with fewer people there may be less of a chance of "Not in my backyard" (NIMBY) kind opposition that has halted so many projects in the past. Selected cities People per square kilometer Potential wind power sites

9 Conclusions & Recommendations This analysis used social and physical constraints, preferences of proximity, and area size to identify suitable lands for wind power development and the top five cities best positioned to harness Montana s wind power and transition to a clean energy economy. While the thoughts and reasons behind the analysis may be sound, the analysis process itself contains limitations. One of these limitations is error and uncertainty. The primary source of error here is resolution; the data I used in this analysis generalize the landscape into 400 m x 400 m cells, which means that any feature smaller than this will not appear in the data. I was constrained by three major limitations in this study. First, I had the locations of transmission lines, but no way of knowing their capacity or current loads. If I had had access to this kind of information, I would have been able to start to assess which wind farm sites could use the existing grid and which needed new transmission lines. Second, I was limited by the tool that calculates a possible path from a potential site to the city center. Instead of being able to calculate the most efficient of all possible paths, this tool finds a path like a river, moving on a cell-by-cell basis on the easiest route. Without the forethought that humans have, this tool is unable to calculate the best possible path from the site to the city. Third, the weight I gave to certain criteria over others was primarily arbitrary, since I am not an expert in the field of siting wind turbines or transmission lines. This study is a good start to what should be a much more thorough analysis of site suitability in Montana. The sites identified here provide not definitive answers, but rather guidelines as to where to start looking in the field. The best course of action from here would be extensive field work in which the results of this type of analysis are ground-truthed. Future work ought to also look for site suitability beyond the boundaries of Montana into Canada and surrounding states. Future work also ought to begin to examine how Montana could not only incorporate wind into its own energy portfolio, but how it could export this renewable energy to other states and Canada. Future work ought to also explore the incorporation of wind energy into the energy portfolio on the scale of individual homes and net metering, as well as on the larger scale of revamping the entire national grid to accommodate local small-scale and large-scale renewable energy production.