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Probabilistic decision model of wind power investment and influence of green power market

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  • Gillenwater, Michael

Abstract

This paper presents results from a model of a representative wind power investor's decision making process using a Monte Carlo simulation of a project financial analysis. Data, in the form of probability distribution functions (PDFs) for key input variables were collected from interviews with investors and other professionals active in the U.S. wind power industry using a formal expert elicitation protocol. This study presents the first quantitative estimates of the effect of the U.S. voluntary Renewable Energy Certificate (REC) market on renewable energy generation. The results indicate that the investment decisions of wind power project developers in the United States are unlikely to have been altered by the voluntary REC market. The problem with the current voluntary REC market is that it does not offer developers a reliable risk-adjusted revenue stream. Consequently, the claims by U.S. green power retailers and promoters that voluntary market RECs result in additional wind power projects lack credibility. Even dramatic increases in voluntary market REC prices, in the absence of long-term contracts, were found to have only a small effect on investor behavior.

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  • Gillenwater, Michael, 2013. "Probabilistic decision model of wind power investment and influence of green power market," Energy Policy, Elsevier, vol. 63(C), pages 1111-1125.
    • Handle: RePEc:eee:enepol:v:63:y:2013:i:c:p:1111-1125
    DOI: 10.1016/j.enpol.2013.09.049
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    2. Elena Verdolini & Laura Díaz Anadón & Erin Baker & Valentina Bosetti & Lara Aleluia Reis, 2018. "Future Prospects for Energy Technologies: Insights from Expert Elicitations," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 133-153.
    3. Nan Shang & Guori Huang & Yuan Leng & Jihong Zhang & Angxing Shen, 2023. "Time Limit of Environmental Benefits of Renewable Energy Power Projects—Analysis Based on Monte Carlo Simulation," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
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    5. Sarah Hafner & Olivia James & Aled Jones, 2019. "A Scoping Review of Barriers to Investment in Climate Change Solutions," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    6. Gillenwater, Michael & Lu, Xi & Fischlein, Miriam, 2014. "Additionality of wind energy investments in the U.S. voluntary green power market," Renewable Energy, Elsevier, vol. 63(C), pages 452-457.
    7. Galzi, Pierre-Yves, 2023. "Do green electricity consumers contribute to the increase in electricity generation capacity from renewable energy sources? Evidence from France," Energy Policy, Elsevier, vol. 179(C).
    8. Nicu Bizon & Phatiphat Thounthong, 2020. "Energy Efficiency and Fuel Economy of a Fuel Cell/Renewable Energy Sources Hybrid Power System with the Load-Following Control of the Fueling Regulators," Mathematics, MDPI, vol. 8(2), pages 1-22, January.
    9. Ivan Ruiz Manuel & Kornelis Blok, 2023. "Quantitative evaluation of large corporate climate action initiatives shows mixed progress in their first half-decade," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    10. Curran, Louise & Lv, Ping & Spigarelli, Francesca, 2017. "Chinese investment in the EU renewable energy sector: Motives, synergies and policy implications," Energy Policy, Elsevier, vol. 101(C), pages 670-682.
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    12. Jaroslava Janekova & Jana Fabianova & Andrea Rosova, 2016. "Environmental And Economic Aspects In Decision Making Of The Investment Project “Wind Park”," Polish Journal of Management Studies, Czestochowa Technical University, Department of Management, vol. 13(1), pages 90-100, June.

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