The research on microgrid power scheduling is more in the direction of microgrid systems, distributed energy scheduling, etc. Dhiman G (2020) [12] proposed a novel hybrid multi
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To conduct research on optimal scheduling of microgrids with coordinated long-term and short-term energy storage, this paper first constructs a wind-PV‑hydrogen microgrid system and
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To address these issues, this paper presents a microgrid scheduling strategy based on the Non—Dominated Sorting Dung Beetle Optimization Algorithm (NSDBO).
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In this regard, a multi-objective optimization scheduling model for microgrids in grid-connected mode is proposed, which comprehensively considers the operational costs and environmental protection
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This study focuses on the optimal scheduling problem of microgrids and proposes a microgrid optimal scheduling model in grid-connected mode, which considers bot
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In this paper, the dynamic optimal scheduling problem of microgrid in island operation is studied, and a multiobjective optimal scheduling model considering operating cost and environmental
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In recent years, microgrid energy optimization scheduling based on deep reinforcement learning (DRL) has made significant progress. With the development of the microgrid, the drawbacks
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To address the shortcomings of the traditional honey badger algorithm in complex microgrid optimization and scheduling problems, such as slow convergence and susceptibility to
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The research results can provide theoretical support and practical reference for efficient scheduling and intelligent optimization of microgrids in the future.
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A multi-strategy Improved Multi-Objective Particle Swarm Algorithm (IMOPSO) method for microgrid operation optimization is proposed for the coordinated optimization problem of microgrid
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