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Roles of diffusion patterns, technological progress, and environmental benefits in determining optimal renewable subsidies in the US

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  • Tibebu, Tiruwork B.
  • Hittinger, Eric
  • Miao, Qing
  • Williams, Eric

Abstract

In this paper we develop an integrated model to identify optimal subsidy schedules for clean energy technologies that maximize social benefits less subsidy costs. The model uses historical cost, adoption, and emissions data and accounts for both environmental and technological progress benefits of the subsidy. An alternative analytical model is also presented to analyze key technological features affecting subsidy design. We focus on three important factors in determining the social benefits of subsidizing the use of clean energy technology: the price (or cost) sensitivity of adoption, induced cost reductions through learning, and environmental benefits. We quantify how distinct profiles of these three factors result in qualitatively different optimal subsidy plans for utility wind and residential solar power in 13 electricity grid regions in the US. Results show that optimal subsidy schedules for utility wind depend on the region, starting at $20–60/MWh, and are roughly constant over time. In contrast, optimal residential solar subsidies either decline over time (starting from $8–70/MWh) or are not desirable (subsidy of zero). The results imply that the optimal subsidy for utility wind is justified mainly through the direct environmental benefits, unlike residential solar PV in which the subsidy is primarily justified by indirect technological progress benefits.

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  • Tibebu, Tiruwork B. & Hittinger, Eric & Miao, Qing & Williams, Eric, 2022. "Roles of diffusion patterns, technological progress, and environmental benefits in determining optimal renewable subsidies in the US," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:tefoso:v:182:y:2022:i:c:s004016252200364x
    DOI: 10.1016/j.techfore.2022.121840
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    1. Fischer, Carolyn & Newell, Richard G., 2005. "Environmental and Technology Policies for Climate Change and Renewable Energy," Discussion Papers 10789, Resources for the Future.
    2. Arthur van Benthem & Kenneth Gillingham & James Sweeney, 2008. "Learning-by-Doing and the Optimal Solar Policy in California," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 131-152.
    3. Wand, Robert & Leuthold, Florian, 2011. "Feed-in tariffs for photovoltaics: Learning by doing in Germany?," Applied Energy, Elsevier, vol. 88(12), pages 4387-4399.
    4. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    5. Jonathan E. Hughes & Molly Podolefsky, 2015. "Getting Green with Solar Subsidies: Evidence from the California Solar Initiative," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 2(2), pages 235-275.
    6. Williams, Eric & Hittinger, Eric & Carvalho, Rexon & Williams, Ryan, 2017. "Wind power costs expected to decrease due to technological progress," Energy Policy, Elsevier, vol. 106(C), pages 427-435.
    7. Chowdhury, Sanjeeda & Sumita, Ushio & Islam, Ashraful & Bedja, Idriss, 2014. "Importance of policy for energy system transformation: Diffusion of PV technology in Japan and Germany," Energy Policy, Elsevier, vol. 68(C), pages 285-293.
    8. Gnann, Till & Stephens, Thomas S. & Lin, Zhenhong & Plötz, Patrick & Liu, Changzheng & Brokate, Jens, 2018. "What drives the market for plug-in electric vehicles? - A review of international PEV market diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 158-164.
    9. Sarzynski, Andrea & Larrieu, Jeremy & Shrimali, Gireesh, 2012. "The impact of state financial incentives on market deployment of solar technology," Energy Policy, Elsevier, vol. 46(C), pages 550-557.
    10. Williams, Eric & Carvalho, Rexon & Hittinger, Eric & Ronnenberg, Matthew, 2020. "Empirical development of parsimonious model for international diffusion of residential solar," Renewable Energy, Elsevier, vol. 150(C), pages 570-577.
    11. Riddhi Panse & Vinish Kathuria, 2015. "Modelling Diffusion Of Wind Power Across Countries," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-36.
    12. Matteson, Schuyler & Williams, Eric, 2015. "Learning dependent subsidies for lithium-ion electric vehicle batteries," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 322-331.
    13. Newbery, David, 2018. "Evaluating the case for supporting renewable electricity," Energy Policy, Elsevier, vol. 120(C), pages 684-696.
    14. Nicolini, Marcella & Tavoni, Massimo, 2017. "Are renewable energy subsidies effective? Evidence from Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 412-423.
    15. Hitaj, Claudia & Löschel, Andreas, 2019. "The impact of a feed-in tariff on wind power development in Germany," Resource and Energy Economics, Elsevier, vol. 57(C), pages 18-35.
    16. Newell, Richard G. & Pizer, William A. & Raimi, Daniel, 2019. "U.S. federal government subsidies for clean energy: Design choices and implications," Energy Economics, Elsevier, vol. 80(C), pages 831-841.
    17. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
    18. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
    19. Tibebu, Tiruwork B. & Hittinger, Eric & Miao, Qing & Williams, Eric, 2021. "What is the optimal subsidy for residential solar?," Energy Policy, Elsevier, vol. 155(C).
    20. Steven E. Sexton & A. Justin Kirkpatrick & Robert Harris & Nicholas Z. Muller, 2018. "Heterogeneous Environmental and Grid Benefits from Rooftop Solar and the Costs of Inefficient Siting Decisions," NBER Working Papers 25241, National Bureau of Economic Research, Inc.
    21. Neij, Lena, 1997. "Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology," Energy Policy, Elsevier, vol. 25(13), pages 1099-1107, November.
    22. Macintosh, Andrew & Wilkinson, Deb, 2011. "Searching for public benefits in solar subsidies: A case study on the Australian government's residential photovoltaic rebate program," Energy Policy, Elsevier, vol. 39(6), pages 3199-3209, June.
    23. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    24. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    25. Dong, Changgui & Sigrin, Benjamin & Brinkman, Gregory, 2017. "Forecasting residential solar photovoltaic deployment in California," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 251-265.
    26. Klaassen, Ger & Miketa, Asami & Larsen, Katarina & Sundqvist, Thomas, 2005. "The impact of R&D on innovation for wind energy in Denmark, Germany and the United Kingdom," Ecological Economics, Elsevier, vol. 54(2-3), pages 227-240, August.
    27. Wiser, Ryan & Pickle, Steven & Goldman, Charles, 1998. "Renewable energy policy and electricity restructuring: a California case study," Energy Policy, Elsevier, vol. 26(6), pages 465-475, May.
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