Wang, H, Shi, M, Xie, P et al. (2 more authors) (2022) Optimal operating regime of an electric vehicle aggregator considering reserve provision. Energy Reports, 8 (Supplement 5). pp. 353-362. ISSN 2352-4847
Abstract
The number of electric vehicles (EVs) is growing rapidly due to environmental concerns and political supports. To better coordinate the charging behaviors of large numbers of EVs, the EV aggregator is an important intermediate between the electricity market and the EVs. This work proposes a two-stage optimal operational regime for an EV aggregator who participates in multiple markets under multiple uncertainties. In the day-ahead stage, a joint offering model is proposed to help the aggregator concurrently participate in both the energy and reserve markets under market price uncertainties. The concept of reserve capacity ratio is introduced in the joint offering model to allow different decisions for aggregators with various risk preferences. In the real-time stage, a rolling horizon control-based multi-resolution scheduling model is proposed to minimize the energy deviation cost under reserve deployment uncertainty. The uncertainties are modeled using representative scenarios and the stochastic optimization approach is applied to acquire the optimal solutions. The numerical results suggest that the proposed operational regime can significantly improve the profitability of the studied EV aggregator. The impact of reserve capacity ratios is also analyzed.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | EV aggregator, Energy and reserve markets, Reserve capacity ratios, Reserve deployment uncertainty, Multi-stage, Multi-resolution |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Oct 2022 10:50 |
Last Modified: | 25 Jun 2023 23:07 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.egyr.2022.02.163 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:192259 |