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GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State

Listed author(s):
  • van Haaren, Rob
  • Fthenakis, Vasilis
Registered author(s):

    Twenty states plus the District of Columbia now have renewable portfolio standards (RPS) in place that requires a certain percentage of energy to come from renewable sources by a specific year. With renewable energy on the verge of massive growth, much research emphasis is put on enabling the implementation of these technologies. This paper presents a novel method of site selection for wind turbine farms in New York State, based on a spatial cost-revenue optimization. The algorithm used for this is built in ESRI ArcGIS Desktop 9.3.1 software and consists of three stages. The first stage excludes sites that are infeasible for wind turbine farms, based on land use and geological constraints. The second stage identifies the best feasible sites based on the expected net present value from four major cost and revenue categories that are spatially dependent: revenue from generated electricity, costs from access roads, power lines and land clearing. The third stage assesses the ecological impacts on bird and their habitats. The proposed spatial multi-criteria methodology is then implemented in New York State and the results were compared with the locations of existing wind turbine farms. The wind farm site selection tool presented in this paper provides insights into the most feasible sites for a large geographic area based on user inputs, and can assist the planning of wind developers, utilities, ISO's and State governments in attaining renewable portfolio standards.

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    Article provided by Elsevier in its journal Renewable and Sustainable Energy Reviews.

    Volume (Year): 15 (2011)
    Issue (Month): 7 (September)
    Pages: 3332-3340

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    Handle: RePEc:eee:rensus:v:15:y:2011:i:7:p:3332-3340
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    1. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
    2. Ramírez-Rosado, Ignacio J. & García-Garrido, Eduardo & Fernández-Jiménez, L. Alfredo & Zorzano-Santamaría, Pedro J. & Monteiro, Cláudio & Miranda, Vladimiro, 2008. "Promotion of new wind farms based on a decision support system," Renewable Energy, Elsevier, vol. 33(4), pages 558-566.
    3. Krohn, Søren & Damborg, Steffen, 1999. "On public attitudes towards wind power," Renewable Energy, Elsevier, vol. 16(1), pages 954-960.
    4. Eltham, Douglas C. & Harrison, Gareth P. & Allen, Simon J., 2008. "Change in public attitudes towards a Cornish wind farm: Implications for planning," Energy Policy, Elsevier, vol. 36(1), pages 23-33, January.
    5. Baban, Serwan M.J & Parry, Tim, 2001. "Developing and applying a GIS-assisted approach to locating wind farms in the UK," Renewable Energy, Elsevier, vol. 24(1), pages 59-71.
    6. Aydin, Nazli Yonca & Kentel, Elcin & Duzgun, Sebnem, 2010. "GIS-based environmental assessment of wind energy systems for spatial planning: A case study from Western Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 364-373, January.
    7. Kaldellis, J. K., 2005. "Social attitude towards wind energy applications in Greece," Energy Policy, Elsevier, vol. 33(5), pages 595-602, March.
    8. Gillenwater, Michael, 2008. "Redefining RECs--Part 1: Untangling attributes and offsets," Energy Policy, Elsevier, vol. 36(6), pages 2109-2119, June.
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