Kristina DiSanto December 6, 2011 NRS 509 GIS and Siting Renewable Energy With our nation s increasing use of technology, expanding industrialization and urbanization to meet our demands for goods and services, we re increasing our demand for electricity. As a result, our fossil fuel consumption is increasing and our natural resources are deteriorating. Transitioning to a more sustainable use of our resources and development techniques may require tapping into renewable energy resources for electricity generation. Among these can include wind, solar, hydro, and bioenergy. Not only will this reduce our fossil fuel demand, but it will increase our energy independence and security. For such reasons, the implementation of these projects is becoming more common and attractive in state energy policies and plans. In many cases, however, after a project is proven economically feasible with minimal land use impacts, the threat of public acceptability still stands. Incorporating the analytical and communicative tools of a Geographic Information System (GIS) for siting renewable energy projects to local and regional decision makers can enable more informed decisions and increase integration of renewable energy technologies into our electric grid (Voivontas 1998). Siting renewable energy projects on a municipal or regional scale is a spatial planning problem that requires accurate economic, social, and environmental impact analyses that are dependent almost entirely on geospatial data. The planning also requires an extensive stakeholder process to engage stakeholders, decision makers, and energy planners and gain full support for project implementation. These parties need to have as much information about the projects as possible and presented in a non technical way that anyone in the general public can understand. Generally, this would involve a map representation of technical data and an effective way to distribute these maps (Simao 2009). Using GIS as a framework allows one to collect and store necessary siting data, use tools to complete spatial analyses and highlight spatial interactions between data sets, and establish an interactive end product that can be distributed on a network of multiple mediums and generalized devises (Clarke 1996). Using GIS as a platform for siting and implementing renewable energy projects began in the 1990s. Over the past two decades, there has been immense progress on the tools developed for use in this field. Typically, a GIS for renewable energy resources is classified into three major groups. The first is the development of a multi criteria spatial decision support system (MCSDSS). A MCSDSS looks at such things as evaluating the potential for resource extraction based on availability, quantifying reductions in CO 2 emissions, and socioeconomic feasibility studies. It basically looks to determine the potential sites in a focus area to install the technology and predicts the environmental and economic impacts (Dominguez 2007). It is in this stage that a GIS database is established and manipulated which first, of course, requires geospatial data that will consist of both raster and vector format. Using the example of wind energy, the most common dataset used is the digital elevation model (DEM) in raster format as elevation is crucial to wind siting with higher wind speeds occurring at higher elevations. Additional items include land use and land cover vector data since turbines cannot be installed
on certain land types such as wetlands. Other data includes digital maps of wind speed regions, coastlines, altitudes, slopes, hydrology, and ecology data. Many studies have also brought in airport, grid networks, and other archaeological site shapefiles. Others have made use of demographic data and energy consumption and demand data to complete a supply demand analysis and determine the most cost effective areas for turbines based on the need for electricity production. Overall, one must be sure to capture all of the data that may affect the potential to install the turbines. Many studies have referred to this type of data as wind farm location criteria (WFLC) to apply spatial analysis (Baban 2001). After gathering the data, many previous researchers in the field have used the wind speed data and other energy supply demand data to create new digital map layers. The way to do this is to have each region of a different wind speed, consumption, or demand level represented as a polygon. It is the purpose of the MSDSS to take data and model it as region objects in order to eventually compute more accurate overlay procedures. A major component of this process is to make sure that all criteria data is transformed into georeferenced objects based on their geographic relation and attributes (Voivontas 1998). The second classification for the use of GIS in renewable energy resource siting is distributed electricity generation. It builds off of the decision support system which creates and manipulates a dataset and further works to determine optimum locations for the technology given specific restrictions on the dataset (Tiba 2010). It completes this type of analysis with tools that already exist within a GIS framework. One of the most common analyses used in siting wind energy is the buffer analysis. For example, one must look at the proximity to airports, archaeological sites, and grid networks. Additional tools used are surface and aspect modules on an elevation model and additional distance operations. One can also apply topology rules and restrictions to the WFLC in the dataset. These could include setting potential turbines in areas according to minimum allowable wind speeds, minimum distance from other geographic objects, and altitude and slope requirements (Voivontas 1998). Lastly, a very crucial step to the siting process which uses GIS is the final overlay procedure to choose the most optimal site. Previous studies have allocated weights to data layers and scores for particular attributes combined with the topology rules to help mark potential sites. Once these weights are assigned, the add function and overlay module in GIS is used to combine the layers and choose the best locations based on WFLC (Baban 2001). The third major group references decentralized generation and rural electrification. This serves, in a sense, as one of the final steps for a GIS tool in the renewable energy siting process. It looks to creating a network for electricity production where electricity is generated at multiple sites but feeds into one grid for distribution. This component would use the same tools as the first two major groups but looks at the technology as an autonomous system and not just individual projects (Tiba 2010). There already exist multiple GIS tools and programs that use GIS as a framework in the renewable energy field for both site analysis and the presentation of technical information. For example, SOLARGIS is a GIS tool that studies the possibility of decentralized generation with renewable resources by using spatial analyses and topology restrictions in a dataset of criteria to find the most optimal locations for extraction. The Renewable Energy Atlas of the West is a second tool that is accessible to the general public over the web. It provides data through an interactive map with information on renewable energy technologies and potential sites for 11
Western states in the U.S. A third example of a GIS tool is NREL, which is also completely accessible via web with data models on solar irradiation to site the potential for solar projects. It also allows users to view different levels of spatial resolution (Tiba 2010). These tools elaborate the idea that not only is it important to provide this type of information to decision makers, stakeholders, and energy planners, but to do so in a user friendly manner and on different mediums. Designing an interactive online map similar to what has been accomplished with the mentioned tools, and offering complete instructions to navigate the site and manipulate its settings, provides information in layman s terms for informed decision making. A more current and local example of using GIS to site renewable energy resources is the Rhode Island Renewable Energy Siting Partnership (RESP). This project began in August 2011 and congregates a URI team of academics and professionals in the energy field consisting of staff at the URI Outreach Center, the Environmental Data Center, the Department of Environmental and Natural Resource Economics, and the Coastal Resources Center. The team will develop guidelines for Rhode Island municipalities to site and manage potential installations of wind, hydropower, and solar photovoltaic projects. Final deliverables for the project include an interactive web portal using GIS mapping tools containing all information necessary for siting these projects. The final database will consist of energy supply and demand information for the state from National Grid and Environment Northeast (ENE) along with spatial and geographic data related to the requirements and restrictions for renewable energy siting, synonymous with previously mentioned datasets. The RESP team is also providing a stakeholder process including monthly meetings, field trips, and supplementary working groups. This follows the theme described by many researchers that spatial planning should involve providing as much information to stakeholders as possible in order to manage and increase public acceptability for the installation of renewable energy projects. This process will also allow the public to preview the GIS tools used for the interactive web portal before it is posted online at the end of March 2012. Working on this project as a graduate assistant at the URI Outreach Center while simultaneously learning about the technical tools of GIS, has exposed me to the many benefits of a GIS in the field of renewable energy. I especially think that GIS is crucial to my field because of the fact that it is, in a sense, a social science problem. These types of projects will not be implemented solely based on the fact that they are economically feasible and beneficial to our future environments. The general public must agree with these installations in order for them to occur. It seems as if the way for this to happen is to present them in the most informative and user friendly way possible. Providing the public with the opportunity to use GIS tools to manipulate the data themselves and input their preferences into the database allows them to feel like they have a say in the process. Although GIS seems to be growing in popularity in reference to this field, there is still room for improvement to make siting even easier. The most difficult aspect of this work is collecting and building the original database. Collecting data at a favorable resolution level, especially in such a small state as Rhode Island, can be both time consuming and extremely expensive. Also, to have a web portal using GIS technology with this type of data continuously updated is an even bigger problem. There is room for GIS to expand as a storing hub for in situ data. There also needs to be established a convenient way for energy consumption and spatial information related to the siting of renewable energy technology to be automatically updated
from sensors in the state. Doing so will not only advance measurements in the field and the integration of renewable energy into our grid, but prove GIS to be an even more favorable tool for this work. Annotated Bibliography Baban, Serwan M.J., and Parry, Tim. 2001. Developing and applying a GIS assisted approach to locating wind farms in the UK. Renewable Energy 24: 59 71. This paper explores the tools within a GIS that can be used to assess the potential for renewable energy projects with a specific focus on the manipulation of wind farm location criteria (WFLC). The authors explain the process of creating constraint factors, or topology rules, within a geodatabase for specific WFLC and using an overlay function coupled with weighting of criteria to mark optimal wind farm sites. They do an excellent job of explaining the process and end benefits of considering all data layers with equal importance and assigning equal weights, then assigning different weights to each of the criterion to determine the optimal siting locations. Unlike some of the other papers I ve found, it closes by referencing the need of a GIS to further improve this process and the accuracy of siting by including a more rapid and improved collection and storage of in situ data. Clarke, J.A. and Grant, A.D. 1996. Planning Support Tools for the Integration of Renewable Energy at the Regional Level. Energy Systems Division, University of Strathclyde. This paper begins by explaining the obstacle of capturing public acceptability for the implementation of renewable energy projects. They offer the idea to create a system in which decision makers are exposed to the potential economic, social, and environmental impacts of a project as well as energy supply and demand profiles of proposed locations to serve as a solution to this problem. This solution essentially involves the use of a GIS framework. What s most favorable about this paper is how they explain the benefits of using a tool that is GIScompatible through a system example, EnTrack, which works as a decision support system. The authors explain what a GIS tool can produce from this type of system in order to present information to decision makers in a user friendly way. Dominguez, Javier and Amador, Julio. 2007. Geographical information systems applied in the field of renewable energy sources. Science Direct, Computers & Industrial Engineering 52: 322 326. Dominguez and Amador introduce information on the ways in which GIS can be applied to improve energy planning and the integration of renewable energy into an electricity grid. They analyze the main contributions of GIS to this field by explaining its application in three concise groups. These groups consist of GIS as part of a decision support system (DSS), to evaluate
opportunities for distributed electricity generation and connection to a grid network, and for planning decentralized production systems. Although the paper does not offer precise detail on specific analytical tools within a GIS to apply to these three groups, they are fairly organized and offer a general, yet useful overview of each group. This allows the reader to understand how different problems within the renewable energy field can apply to a certain application type within a GIS. Ramachandra, T.V. and Shruthi, B.V. 2007. Spatial mapping of renewable energy potential. Science Direct, Renewable and Sustainable Energy Reviews 11: 1460 1480. This paper explains the value behind GIS in renewable energy resource siting problems and suggests the use of the tool for energy supply demand matching. They explain that an accurate assessment of these projects requires a spatial analysis of available resources, which is most easily completed within a GIS. They explain these concepts and the benefits of using GIS through a case study in which they assess the potential for solar, wind, hydro, and bioenergy in Karnataka State, India. In their methodology section, they explain how the general GIS tool was used to identify and quantify constraints on the potential for these projects and enhance their database. Perhaps the best section of the paper was their literature review offering insight to work previously completed in this area and the ways in which other researchers in the energy field have used a GIS. Simao, Ana, Densham, Paul J., and Haklay, Mordechai. 2009. Web based GIS for collaborative planning and public participation: An application to the strategic planning of wind farm sites. Journal of Environmental Management 90: 2027 2040. This paper offers an elaborate explanation of the need for a spatial decision support system to aid energy planning and managing, especially in that of renewable energy. Simao et al. give a detailed discussion on the stakeholder process involved in spatial planning and the need for all parties involved in or impacted by the implementation of renewable energy projects to have complete information in order to be fully engaged. The authors mention that this process requires both maps with information and an effective means of communication. They use a wind farm siting case study to prove that a GIS based framework can provide both of these requirements. The best part about this paper is that they offer a detailed description for the design of their program and the role of specific GIS tools to create and maintain data as well as the tools that users can take advantage of when viewing the program. Tiba, C. Candeias, A.L.B, Fraidenraich, N., Barbosa, E.M., Carvalho Neto, P.B., and Melo Filho, J.B. 2010. A GIS based decision support tool for renewable energy management and planning in semi arid rural environments of northeast of Brazil. Renewable Energy 35: 2921 2932. Tiba et al, referencing a study area for assessing the potential for solar and biomass energy, offer a solid but brief overview of the qualitative benefits of a GIS tool for siting renewable energy including reference to some of the first projects in the 1990s. The particularly useful thing about this paper was its reference to the three common classified groups for GIS in renewable energy and then specific GIS programs implemented for the purpose of siting, many of which are available online for the general public to use.
Voivontas, D., Assimacopoulos, D., and Mourelatos, A. 1998. Evaluation of Renewable Energy Potential Using a GIS Decision Support System. Renewable Energy 13: 333 344. Voivontas et al use wind data from the island of Crete in Greece as a case study to evaluate the potential for wind energy with a decision support system in a GIS. This paper was meant to serve as one of the first to explain the benefits of a GIS database and specific spatial analysis functions of a GIS tool in measuring the feasibility of wind turbine installations. The paper offers insight into the type of data that can be downloaded and enriched in a GIS database specifically for wind turbine projects. Not only does it do a favorable job of explaining specific parts and actions completed by a data manager in GIS, it keeps in mind the big picture of how energy projects should be based off of a spatial evaluation of demand and other geographic attributes.