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Impact of Penalty Structures on Virtual Power Plants in a Day-Ahead Electricity Market

Author

Listed:
  • Youngkook Song

    (Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea)

  • Myeongju Chae

    (Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea)

  • Yeonouk Chu

    (Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea)

  • Yongtae Yoon

    (Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea)

  • Younggyu Jin

    (Power System Economics Laboratory, Department of Electrical Engineering, Jeju National University, Jeju 62343, Republic of Korea)

Abstract

The rapid increase in distributed energy resources has augmented the significance of virtual power plants (VPPs), which are essential for the aggregation and management of variable renewable energy resources (RERs). The inherent variability and uncertainty of RERs necessitate the implementation of deviation penalties to address the discrepancies between the awarded bids and actual generation, which is crucial in maintaining market stability and ensuring reliable grid operations. Therefore, this study proposes a framework for deviation penalty structures, categorizing penalties based on three factors: the penalty scope, penalty rate, and penalty coefficient. The simulation results show that the penalty scope significantly influences the revenue of VPPs, with over-generation penalty structures typically yielding higher profitability. Conversely, dual-sided penalty structures result in lower total revenues compared to one-sided penalty structures. For instance, when the penalty price coefficient is set to 0.1, the total revenue of a dual-sided penalty structure is approximately 62.26% lower than that of a one-sided penalty structure during the morning period. The results also demonstrate that deviation penalty structures have a direct impact on power deviations and curtailment behavior. Finally, we offer recommendations for the design of an effective penalty structure aimed at assisting policymakers and distributed system operators (DSOs) in structuring market mechanisms, which not only facilitate the integration of RERs but also enhance their economic viability within electricity markets.

Suggested Citation

  • Youngkook Song & Myeongju Chae & Yeonouk Chu & Yongtae Yoon & Younggyu Jin, 2024. "Impact of Penalty Structures on Virtual Power Plants in a Day-Ahead Electricity Market," Energies, MDPI, vol. 17(23), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:6042-:d:1534404
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    References listed on IDEAS

    as
    1. Jia, Dongqing & Li, Xingmei & Gong, Xu & Lv, Xiaoyan & Shen, Zhong, 2024. "Bi-level strategic bidding model of novel virtual power plant aggregating waste gasification in integrated electricity and hydrogen markets," Applied Energy, Elsevier, vol. 357(C).
    2. Tang, Qinghu & Guo, Hongye & Zheng, Kedi & Chen, Qixin, 2024. "Forecasting individual bids in real electricity markets through machine learning framework," Applied Energy, Elsevier, vol. 363(C).
    3. Fusco, Andrea & Gioffrè, Domenico & Francesco Castelli, Alessandro & Bovo, Cristian & Martelli, Emanuele, 2023. "A multi-stage stochastic programming model for the unit commitment of conventional and virtual power plants bidding in the day-ahead and ancillary services markets," Applied Energy, Elsevier, vol. 336(C).
    4. Zhang, Tianhan & Qiu, Weiqiang & Zhang, Zhi & Lin, Zhenzhi & Ding, Yi & Wang, Yiting & Wang, Lianfang & Yang, Li, 2023. "Optimal bidding strategy and profit allocation method for shared energy storage-assisted VPP in joint energy and regulation markets," Applied Energy, Elsevier, vol. 329(C).
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