Zhao, S, Li, K orcid.org/0000-0001-6657-0522, Yang, Z et al. (2 more authors) (2022) A new power system active rescheduling method considering the dispatchable plug-in electric vehicles and intermittent renewable energies. Applied Energy, 314. 118715. ISSN 0306-2619
Abstract
The significant penetration of renewable power generations (RGs) and the large-scale use of plug-in electric vehicles (PEVs) have brought tangible impacts in tackling the climate change challenge the mankind has been facing due to substantive green-house gas and pollutant emissions from fossil-fuel based thermal power generation plants. However, the uncertainty of RGs has also exerted significant challenges to the grid operation and control. Therefore, dynamic power system scheduling to accommodate the intermittent RGs and mass roll-out of PEVs has become extremely important. In this paper, a novel power system rescheduling strategy is proposed to tackle this problem. Considering the uncertainty of the wind energy, a set of indices according to different wind power application scenarios is proposed to initiate a rescheduling scheme for power generations. In addition, a social learning particle swarm optimization algorithm based on real-value and binary parallel is proposed to schedule the output of generator units and the charging and discharging of the PEV. The effectiveness of the proposed active rescheduling framework and solving algorithm has been verified by extensive experiments considering different number of generating units and scenarios, achieving up to over 5.3% cost reduction. The experimental results have also shown that through expropriate management of the charging and discharging of PEVs would be significantly alleviate the negative impact on the grid stability caused by the intermittent wind power generations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Applied Energy made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0) in accordance with the publisher's self-archiving policy. |
Keywords: | Unit commitment; Electric vehicle; Renewable energy; Rescheduling scheme |
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) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Feb 2022 11:48 |
Last Modified: | 23 Mar 2023 08:15 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.apenergy.2022.118715 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184060 |