Optimizing EV cluster contribution for vehicle-to-grid(V2G) frequency regulation

Wu, Erbo, Jakubiak, Krzysztof ORCID: https://orcid.org/0000-0003-1195-4697, Wang, Yaoqiang and Liang, Jun ORCID: https://orcid.org/0000-0001-7511-449X 2022. Optimizing EV cluster contribution for vehicle-to-grid(V2G) frequency regulation. Presented at: 57th International Universities Power Engineering Conference (UPEC)MPORTED, MAY BE LINKED, 30 August - 02 September 2022. Proceedings 57th International Universities Power Engineering Conference (UPEC) 2022. IEEE, 10.1109/UPEC55022.2022.9917791

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Abstract

When electric vehicles (EVs) are integrated into the grid for frequency regulation, the energy stored the EVs would be released excessively without a proper schedule. The system cannot appropriately utilize the energy of the generator and EVs. Many studies only focus on frequency stability but ignore the output of EV cluster. Based on this, this paper proposes a control strategy (Fuzzy-PI) that uses fuzzy control to generate a variable coefficient, which is multiplied with the PI control signal as the control signal for the EV cluster. The coefficient can increase or decrease the EV output power depending on the variation of the frequency deviation. In order to contribute an appropriate number of EVs, this paper optimizes the ratio parameter of EVs invested in V2G with the goal of reducing EV cluster output and improving frequency stability. The private cars, buses and taxis are considered for integrating into an EV cluster to participate in the grid auxiliary frequency regulation. A single-area system model for the participation of EV cluster in the micro-grid frequency regulation is established. Finally, by the comparative study of simulation algorithms, the results demonstrate the superiority of EV cluster participation in frequency regulation, as well as the effectiveness of the proposed Fuzzy-PI control and optimization strategy.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	IEEE
ISBN:	978-1-6654-5505-3
Last Modified:	23 Jun 2023 11:45
URI:	https://orca.cardiff.ac.uk/id/eprint/160540

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