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Statistical analysis of installed wind capacity in the United States

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  • Staid, Andrea
  • Guikema, Seth D.

Abstract

There is a large disparity in the amount of wind power capacity installed in each of the states in the U.S. It is often thought that the different policies of individual state governments are the main reason for these differences, but this may not necessarily be the case. The aim of this paper is to use statistical methods to study the factors that have the most influence on the amount of installed wind capacity in each state. From this analysis, we were able to use these variables to accurately predict the installed wind capacity and to gain insight into the driving factors for wind power development and the reasons behind the differences among states. Using our best model, we find that the most important variables for explaining the amount of wind capacity have to do with the physical and geographic characteristics of the state as opposed to policies in place that favor renewable energy.

Suggested Citation

  • Staid, Andrea & Guikema, Seth D., 2013. "Statistical analysis of installed wind capacity in the United States," Energy Policy, Elsevier, vol. 60(C), pages 378-385.
    • Handle: RePEc:eee:enepol:v:60:y:2013:i:c:p:378-385
    DOI: 10.1016/j.enpol.2013.05.076
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    References listed on IDEAS

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    Cited by:

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    2. Hedenus, F. & Jakobsson, N. & Reichenberg, L. & Mattsson, N., 2022. "Historical wind deployment and implications for energy system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Feng, Qianqian & Sun, Xiaolei & Hao, Jun & Li, Jianping, 2021. "Predictability dynamics of multifactor-influenced installed capacity: A perspective of country clustering," Energy, Elsevier, vol. 214(C).
    4. Biresselioglu, Mehmet Efe & Kilinc, Dilara & Onater-Isberk, Esra & Yelkenci, Tezer, 2016. "Estimating the political, economic and environmental factors’ impact on the installed wind capacity development: A system GMM approach," Renewable Energy, Elsevier, vol. 96(PA), pages 636-644.
    5. Ye, Lin & Zhang, Cihang & Xue, Hui & Li, Jiachen & Lu, Peng & Zhao, Yongning, 2019. "Study of assessment on capability of wind power accommodation in regional power grids," Renewable Energy, Elsevier, vol. 133(C), pages 647-662.
    6. Thomas Lauf & Kristina Ek & Erik Gawel & Paul Lehmann & Patrik Söderholm, 2020. "The regional heterogeneity of wind power deployment: an empirical investigation of land-use policies in Germany and Sweden," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 63(4), pages 751-778, March.
    7. Millon, Lara & Barré, Kévin & Julliard, Romain & Compère, Pierre & Kerbiriou, Christian, 2021. "Calculation of biodiversity level between different land-uses to improve conservation outcomes of biodiversity offsetting," Land Use Policy, Elsevier, vol. 101(C).
    8. Charakopoulos, Avraam & Karakasidis, Theodoros & Sarris, loannis, 2019. "Pattern identification for wind power forecasting via complex network and recurrence plot time series analysis," Energy Policy, Elsevier, vol. 133(C).
    9. Thapar, Sapan & Sharma, Seema & Verma, Ashu, 2018. "Key determinants of wind energy growth in India: Analysis of policy and non-policy factors," Energy Policy, Elsevier, vol. 122(C), pages 622-638.

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