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A method for optimizing the location of wind farms

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  • McWilliam, M.K.
  • van Kooten, G.C.
  • Crawford, C.

Abstract

The optimal location and configuration of wind farms in a large region is important information for policy makers, electricity system planners and wind farm developers. The model developed in this paper uses wind resource data, population data and transmission line locations to find the configuration that produces electricity at minimum cost. Several economic and regulatory scenarios were used to demonstrate the importance of each factor in siting optimally siting wind farms. We demonstrate how gradient based optimization could be applied to discover optimal wind farm location and size. Although the use of gradient based optimization makes the model sensitive to local minima, numerical smoothing is used to reduce this sensitivity.

Suggested Citation

  • McWilliam, M.K. & van Kooten, G.C. & Crawford, C., 2012. "A method for optimizing the location of wind farms," Renewable Energy, Elsevier, vol. 48(C), pages 287-299.
    • Handle: RePEc:eee:renene:v:48:y:2012:i:c:p:287-299
    DOI: 10.1016/j.renene.2012.05.006
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Reddy, Sohail R., 2021. "A machine learning approach for modeling irregular regions with multiple owners in wind farm layout design," Energy, Elsevier, vol. 220(C).
    2. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    3. G. Cornelis van Kooten, 2012. "Natural Gas, Wind and Nuclear Options for Generating Electricity in a Carbon Constrained World," Working Papers 2012-01, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    4. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    5. Ribeiro, Alan Emanuel Duailibe & Arouca, Maurício Cardoso & Coelho, Daniel Moreira, 2016. "Electric energy generation from small-scale solar and wind power in Brazil: The influence of location, area and shape," Renewable Energy, Elsevier, vol. 85(C), pages 554-563.
    6. Yeh, Tsu-Ming & Huang, Yu-Lang, 2014. "Factors in determining wind farm location: Integrating GQM, fuzzy DEMATEL, and ANP," Renewable Energy, Elsevier, vol. 66(C), pages 159-169.
    7. Jon Duan & G. Cornelis van Kooten & A. T. M. Hasibul Islam, 2023. "Calibration of Grid Models for Analyzing Energy Policies," Energies, MDPI, vol. 16(3), pages 1-21, January.
    8. Katsaprakakis, Dimitris Al. & Christakis, Dimitris G., 2016. "The exploitation of electricity production projects from Renewable Energy Sources for the social and economic development of remote communities. The case of Greece: An example to avoid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 341-349.
    9. Frank Hanssen & Roel May & Jiska van Dijk & Jan Ketil Rød, 2018. "Spatial Multi-Criteria Decision Analysis Tool Suite for Consensus-Based Siting of Renewable Energy Structures," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-28, September.
    10. G. Cornelis van Kooten, 2015. "All you want to know about the Economics of Wind Power," Working Papers 2015-07, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    11. Miller, Aaron & Chang, Byungik & Issa, Roy & Chen, Gerald, 2013. "Review of computer-aided numerical simulation in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 122-134.
    12. van Kooten, G. Cornelis & Withey, Patrick & Duan, Jon, 2020. "How big a battery?," Renewable Energy, Elsevier, vol. 146(C), pages 196-204.
    13. Wang, Longyan & Tan, Andy C.C. & Gu, Yuantong & Yuan, Jianping, 2015. "A new constraint handling method for wind farm layout optimization with lands owned by different owners," Renewable Energy, Elsevier, vol. 83(C), pages 151-161.
    14. Siyal, Shahid Hussain & Mörtberg, Ulla & Mentis, Dimitris & Welsch, Manuel & Babelon, Ian & Howells, Mark, 2015. "Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach," Energy, Elsevier, vol. 83(C), pages 447-461.
    15. Flora, Rui & Marques, António Cardoso & Fuinhas, José Alberto, 2014. "Wind power idle capacity in a panel of European countries," Energy, Elsevier, vol. 66(C), pages 823-830.

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