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The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets

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  • Moreno, Blanca
  • Díaz, Guzmán

Abstract

Virtual Power Plant combines a wide variety of distributed generation resources and operates them as a unified resource on the energy markets. It gives an economic opportunity to renewable energy-based distributed generation, such as photovoltaic, small hydro or wind, as it can build a bridge to the integration of renewable resources in the wholesale electricity market. In this market, changes in the offers of portfolio electricity technologies affect wholesale electricity prices, since marginal generation costs are transmitted through to the wholesale market.

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  • Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
    • Handle: RePEc:eee:rensus:v:99:y:2019:i:c:p:100-108
    DOI: 10.1016/j.rser.2018.09.028
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    2. Behnaz Behi & Ali Baniasadi & Ali Arefi & Arian Gorjy & Philip Jennings & Almantas Pivrikas, 2020. "Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study," Energies, MDPI, vol. 13(10), pages 1-24, May.
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    7. Behnaz Behi & Ali Arefi & Philip Jennings & Arian Gorjy & Almantas Pivrikas, 2021. "Advanced Monitoring and Control System for Virtual Power Plants for Enabling Customer Engagement and Market Participation," Energies, MDPI, vol. 14(4), pages 1-19, February.
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    15. Han, Chanok & Vinel, Alexander, 2022. "Reducing forecasting error by optimally pooling wind energy generation sources through portfolio optimization," Energy, Elsevier, vol. 239(PB).
    16. Guo-Feng Fan & Yan-Hui Guo & Jia-Mei Zheng & Wei-Chiang Hong, 2019. "Application of the Weighted K-Nearest Neighbor Algorithm for Short-Term Load Forecasting," Energies, MDPI, vol. 12(5), pages 1-19, March.

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