The method integrates multiple RES and optimizes energy storage usage, aiming to reduce operating power costs and improve energy management on both the generation and load sides, all while adhering to system constraints.. The method integrates multiple RES and optimizes energy storage usage, aiming to reduce operating power costs and improve energy management on both the generation and load sides, all while adhering to system constraints.. To achieve the optimal solution between construction costs and carbon emissions in the multi-target optimization scheduling, this paper proposes a multi-objective optimization scheduling design for wind–solar energy storage microgrids based on an improved oppositional gradient grey wolf. . The integration of renewable energy sources (RES) such as wind, solar, and micro turbines into modern power systems presents significant challenges in energy resource scheduling. Efficient optimization is crucial for minimizing operational costs, improving system reliability, and ensuring effective.
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