Multi-objective optimal dispatch of island microgrid considering a novel scheduling resource

•Integrate UPS into island microgrid for enhanced power supply reliability.•Adopt flywheel energy storage for UPS, ensuring rapid response.•Apply multi-objective optimization for economy, environment, satisfaction.•Employ improved algorithm to enhance optimization performance. To alleviate the power...

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Veröffentlicht in:Electric power systems research 2025-04, Vol.241, p.111378, Article 111378
Hauptverfasser: Zhao, Guo, Luo, Jiawen, Song, Ningfeng, Shu, Jun
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Sprache:eng
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Zusammenfassung:•Integrate UPS into island microgrid for enhanced power supply reliability.•Adopt flywheel energy storage for UPS, ensuring rapid response.•Apply multi-objective optimization for economy, environment, satisfaction.•Employ improved algorithm to enhance optimization performance. To alleviate the power supply pressure caused by the proliferation of data centers in island areas and to improve the reliability of off-grid systems, this paper introduces a new type of power dispatch resource called uninterruptible power supply (UPS). To address the incompleteness of single-objective optimization, a three-objective scheduling strategy for island microgrid based on an improved multi-objective particle swarm optimization (IMOPSO) algorithm is proposed, which integrates economic cost, renewable energy utilization and user satisfaction. To improve the search efficiency and solution quality of the algorithm, the parameter adjustment strategy is improved, and the adaptive strategy and fuzzy identification are introduced to realize the acquisition of the optimal solution. The effectiveness of the proposed strategy is substantiated on the MATLAB platform. The cost of the method proposed in this paper is reduced by 11.15 % compared to single objective optimization and satisfaction is improved by 4.76 % compared to traditional system. Better Pareto results are also obtained compared to other algorithms mentioned in this paper.
ISSN:0378-7796
DOI:10.1016/j.epsr.2024.111378