Traditional optimization scheduling in microgrids refers to the real-time monitoring and analysis of the operational status and energy output of various energy components within the microgrid, such as solar panels, wind turbines, and storage systems, to achieve optimal. . Traditional optimization scheduling in microgrids refers to the real-time monitoring and analysis of the operational status and energy output of various energy components within the microgrid, such as solar panels, wind turbines, and storage systems, to achieve optimal. . To this end, this paper proposes an intelligent scheduling framework based on reinforcement learning and data-driven optimization to improve the adaptability of microgrids to uncertainty and multi-objective optimization problems. The research results can provide theoretical support and practical. . given to optimize objective functions in microgrid. The following nd challenging multi-objective optimization proble of the. . Abstract: Microgrid optimization scheduling, as a crucial part of smart grid optimization, plays a significant role in reducing energy consumption and environmental pollution.
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