APSA-based Collaborative Optimization Strategy for Source-Grid-Load-Storage in Coal Mine Microgrids

To address the inherent source-load mismatch in coal mine microgrids under the "dual-carbon" context, this paper proposes a multi-objective collaborative optimization scheduling strategy for Source-Grid-Load-Storage (SGLS). First, a multi-objective collaborative optimization model is constructed, comprehensively considering economy, sustainability, and system stability. For model solving, a three-layer nested optimization framework is designed to find the optimal solution set through layer-by-layer constraint application. Each layer adopts a PID-based meta-heuristic optimization algorithm (PSA). To enhance the performance of the original PSA algorithm and balance its global exploration and local development capabilities, an adaptive parameter adjustment mechanism is designed. Finally, simulation verification is conducted using a coal mine case study. Comparisons with pre-optimization results and other common optimization algorithms demonstrate that this strategy effectively resolves the SGLS collaborative optimization problem in coal mine microgrids, providing an efficient solution for safe, green, and economical operation in mining areas.