Frequency Regulation of Electric Vehicle Aggregator Considering User Requirements with Limited Data Collection

• Published in: Energies (Basel) 2023-01, Vol.16 (2), p.848
• Main Authors: Zeng, Fei, Wei, Zhinong, Sun, Guoqiang, Wang, Mingshen, Han, Haiteng
• Format: Article
• Language: English
• Subjects: Control methods; Data collection; Electric power distribution; electric vehicle (EV); Electric vehicle charging stations; Electric vehicles; Energy; Error correction; EV aggregator; Frequency deviation; frequency regulation; Frequency stability; limited data collection; regulation requirement; Renewable resources; state recovery; Vehicle-to-grid
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16020848

High penetration of renewable energy in the power grid causes serious frequency deviations. Large-scale integrations of electric vehicles (EVs) in the power grid provide considerable vehicle-to-grid potential for frequency regulation. Existing frequency regulation strategies with aggregated EVs realize accurate power control that relies on complete information interaction between the EV aggregator and individual EVs. However, the data collection for all EV parameters is not applicable due to privacy protection and the limited communication environment. Considering the limited data collection from grid-connected EVs, this paper provides a novel frequency regulation strategy and tends to address the uncertain influence from EV users’ charging requirements, the EV aggregator’s power regulation, and the frequency regulation performance. Firstly, considering the influence of the limited data collection by EVs on the users’ requirement of traveling and regulation preference, a probabilistic evaluation model for the available regulation capacity of the EV aggregator and the probabilistic control method for EVs are developed. Then, a frequency regulation strategy with error correction control and progressive regulation recovery is developed to simultaneously guarantee the system frequency regulation performance and the regulation requirements of EV users. Finally, case studies are carried out to validate the effectiveness of frequency regulation strategy for decreasing the uncertain influence from the limited data collection, ensuring the EV users’ requirements, and improving the system frequency stability.