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Simultaneous community energy supply-demand optimization by microgrid operation scheduling optimization and occupant-oriented flexible energy-use regulation

Zhang, Chengyu, Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400, Luo, Zhiwen, Jiang, Ben and Zhao, Tianyi 2024. Simultaneous community energy supply-demand optimization by microgrid operation scheduling optimization and occupant-oriented flexible energy-use regulation. Applied Energy 373 , 123922. 10.1016/j.apenergy.2024.123922
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Abstract

Community microgrids represent a pivotal solution for addressing energy conservation and reducing carbon emissions. However, few studies focused on the methods of concurrently optimizing both the supply and demand sides within campus settings, a unique form of community. Moreover, few studies on energy demand optimization rarely delved into human-centered approaches and employed multi-strategy parallel flexible regulations, while few studies on energy supply optimization discussed the comprehensive environment-energy-society-investment benefits as optimization objectives with suitable algorithms for calculation. Consequently, this study introduced a novel approach to energy system supply-demand optimization by simultaneous flexible energy-use regulation and microgrid operation scheduling, to explore human-centered multi-strategy parallel flexible energy-use regulations, and comprehensive evaluation parameters for energy supply-demand optimization. (1) Regarding flexible energy-use regulation, this study proposed several adjustments including adjusting the start-up temperature of air conditioners (ACs), organized charging of electric vehicles (EVs), light or plug management, and course optimization. These parallel adjustments can reduce or shift 12.12% of energy demand during peak hours and 8.06% during sharp hours, yielding 4.449%–8.820% of the annual average benefits in different cases. (2) Regarding microgrid optimization scheduling, this study introduced novel objectives aimed at maximizing investment-environment-energy-society benefits and solving algorithms, the jellyfish search algorithm (JSA), for calculation. Results showed 10.085%–11.728% of the annual average benefits in different cases. Ultimately, the optimization integration of flexible energy-use regulations and microgrid operation scheduling yields 15.655%–18.016% of the annual average benefits in different cases.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0306-2619
Date of First Compliant Deposit: 18 July 2024
Date of Acceptance: 12 July 2024
Last Modified: 09 Nov 2024 01:45
URI: https://orca.cardiff.ac.uk/id/eprint/170659

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