Optimal Bidding Strategy of Electric Vehicle Aggregators in Energy, Frequency Regulation and Demand Response Market

This paper proposes a comprehensive framework for Electric Vehicle Aggregators (EVAs) bidding in joint markets, namely energy, frequency regulation and Demand Response markets, across both day-ahead and real-time stages. The optimal bidding strategy aims at minimizing the total cost of EVA, while sa...

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Bibliographic Details
Published in2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2) pp. 1975 - 1980
Main Authors Tang, Wenjun, He, Shan, Zhao, Yuming, Xu, Manqi, Guo, Ye
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.12.2023
Subjects
Costs
Demand response
Demand Response market
Electric Vehicle Aggregators
multi-time-scale economic scheduling strategy
optimal bidding strategy
Real-time systems
Regulation
Regulation market
Stochastic processes
System integration
Uncertainty
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Summary:This paper proposes a comprehensive framework for Electric Vehicle Aggregators (EVAs) bidding in joint markets, namely energy, frequency regulation and Demand Response markets, across both day-ahead and real-time stages. The optimal bidding strategy aims at minimizing the total cost of EVA, while satisfying the charging demand of all connected electric vehicles (EVs), To address uncertainties associated with EV parameters and regulation signals, a two-stage stochastic optimization problem based on the aggregated EVs and regulation signal model is formulated. Additionally, a rolling-window method is employed to mitigate uncertainty during the real-time stage. The effectiveness of the proposed method is verified through extensive numerical tests involving 500 EVs, demonstrating its capability to yield lucrative profits while simultaneously satisfying EVs' charging demand.
DOI:10.1109/EI259745.2023.10512941