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Frequency Regulation-Based Optimal Charging Scheduling of EV Clusters Based on Strategical Bidding in Power Market

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Abstract

In this paper, a novel optimal bidding model through charging scheduling of Electric Vehicle (EV) cluster is proposed by considering the battery degradation to participate in the regulation market and energy market by considering Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) mode of operation. By utilizing the higher ramp rate of the EV battery, the participation of EV in performance-based frequency regulation (PBFR) is shown to enhance the profit incurred by parking lot operators (PLO). On the contrary, higher charging/discharging rate of EV battery due to the bidding in frequency regulation (FR) market may degrade the EV battery lifecycle. Hence, in this paper, an optimal bidding has been modeled by incorporating the above-mentioned challenges, which will enhance the PLOs revenue and as well as take care of the battery lifecycle of EV, by incorporating optimization techniques. Along with the bidding strategy, the cruising of EV is taken into contemplation and the cost of charging of EV is minimized. To handle the uncertainty of the EVs state of charge (SOC), 2 m-Point Estimation Method (2 m-PEM) is applied. It can be seen that the proposed algorithm is robust enough to earn revenue performing optimal bidding in power market.

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  1. Department of Electrical Engineering, National Institute of Technology Durgapur, Durgapur, 713209, India

    Sourav Das, Parimal Acharjee & Aniruddha Bhattacharya

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This article is part of the topical collection “Enabling Innovative Computational Intelligence Technologies for IOT” guest edited by Omer Rana, Rajiv Misra, Alexander Pfeiffer, Luigi Troiano and Nishtha Kesswani.

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Das, S., Acharjee, P. & Bhattacharya, A. Frequency Regulation-Based Optimal Charging Scheduling of EV Clusters Based on Strategical Bidding in Power Market. SN COMPUT. SCI. 4, 591 (2023). https://doi.org/10.1007/s42979-023-02012-8

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