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Lessons Learned from Photovoltaic Auctions in Germany

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  • Taimyra Batz Li~neiro
  • Felix Musgens

Abstract

Auctions have become the primary instrument for promoting renewable energy around the world. However, the data published on such auctions are typically limited to aggregated information (e.g., total awarded capacity, average payments). These data constraints hinder the evaluation of realisation rates and other relevant auction dynamics. In this study, we present an algorithm to overcome these data limitations in German renewable energy auction programme by combining publicly available information from four different databases. We apply it to the German solar auction programme and evaluate auctions using quantitative methods. We calculate realisation rates and - using correlation and regression analysis - explore the impact of PV module prices, competition, and project and developer characteristics on project realisation and bid values. Our results confirm that the German auctions were effective. We also found that project realisation took, on average, 1.5 years (with 28% of projects finished late and incurring a financial penalty), nearly half of projects changed location before completion (again, incurring a financial penalty) and small and inexperienced developers could successfully participate in auctions.

Suggested Citation

  • Taimyra Batz Li~neiro & Felix Musgens, 2021. "Lessons Learned from Photovoltaic Auctions in Germany," Papers 2104.07536, arXiv.org.
    • Handle: RePEc:arx:papers:2104.07536
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    1. Shrimali, Gireesh & Konda, Charith & Farooquee, Arsalan Ali, 2016. "Designing renewable energy auctions for India: Managing risks to maximize deployment and cost-effectiveness," Renewable Energy, Elsevier, vol. 97(C), pages 656-670.
    2. repec:aen:journl:ej40-6-welisch is not listed on IDEAS
    3. Cassetta, Ernesto & Monarca, Umberto & Nava, Consuelo Rubina & Meleo, Linda, 2017. "Is the answer blowin' in the wind (auctions)? An assessment of the Italian support scheme," Energy Policy, Elsevier, vol. 110(C), pages 662-674.
    4. Anatolitis, Vasilios & Welisch, Marijke, 2017. "Putting renewable energy auctions into action – An agent-based model of onshore wind power auctions in Germany," Energy Policy, Elsevier, vol. 110(C), pages 394-402.
    5. repec:aen:journl:ej38-si1-madlener is not listed on IDEAS
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