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Analysis of drivers affecting the use of market premium for renewables in Germany

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  • Genoese, Massimo
  • Slednev, Viktor
  • Fichtner, Wolf

Abstract

In this paper, we identify and analyze parameters that determine the profitability of wind power operators in the German market premium model. Based on an empirical analysis of different German wind power profiles from 2007 to mid-2012, we are able to show that the profitability significantly depends on the correlation of the wind power portfolio with the overall wind power feed-in and prediction error in Germany. Significant differences between the wind forecast errors clearing cost of the analyzed portfolios can be identified. Our analysis shows that a wind power operator would profit in most cases from a reduced forecast error, which could be achieved through an improved forecast model and an increased share of the intraday cleared error. Furthermore significant locational portfolio advantages and disadvantages can be identified when comparing the different market values. In general, the empirical analysis shows that a premium of 3.5€/MWh is suitable to cover the cost of an imperfect forecast. Taking further into account that for 2012 a premium of 12€/MWh was granted; the direct marketing option can be evaluated as highly attractive, which is furthermore indicated by the rapid increase of the directly marketed wind power and photovoltaic generation.

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  • Genoese, Massimo & Slednev, Viktor & Fichtner, Wolf, 2016. "Analysis of drivers affecting the use of market premium for renewables in Germany," Energy Policy, Elsevier, vol. 97(C), pages 494-506.
    • Handle: RePEc:eee:enepol:v:97:y:2016:i:c:p:494-506
    DOI: 10.1016/j.enpol.2016.07.043
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    References listed on IDEAS

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    Cited by:

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    3. Hualin Cai & Jiageng Chen & Chenjing Dong & Jing Li & Zhemin Lin & Chuan He & Yicheng Jiang & Jincheng Li & Li Yang, 2019. "Power Market Equilibrium under the Joint FIP-RPS Renewable Energy Incentive Mechanism in China," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    4. Joos, Michael & Staffell, Iain, 2018. "Short-term integration costs of variable renewable energy: Wind curtailment and balancing in Britain and Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 86(C), pages 45-65.
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    6. Engelhorn, Thorsten & Müsgens, Felix, 2018. "How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany," Energy Economics, Elsevier, vol. 72(C), pages 542-557.
    7. Hanemann, Philipp & Bruckner, Thomas, 2018. "Effects of electric vehicles on the spot market price," Energy, Elsevier, vol. 162(C), pages 255-266.

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