Collaborative optimization strategy of source-grid-load-storage for coal mine microgrid based on APSA
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Abstract
Most existing dispatching methods for coal mine power systems adopt a single-objective optimization framework that takes minimization of operating cost as the sole objective and mainly considers static security constraints. However, in practical operation of coal mine energy systems, both dynamic and static security requirements need to be satisfied, and reasonable trade-offs among multiple competing objectives must be achieved. The PID-Based Search Algorithm (PSA) has strong optimization potential, but it is prone to falling into local optima and is difficult to adapt to the complex and variable optimization environment of coal mine microgrids. To address this issue, an adaptive parameter adjustment mechanism was introduced, based on which an Adaptive PID-Based Search Algorithm (APSA) was proposed, and a collaborative optimization model of source-grid-load-storage for coal mine microgrids based on APSA was constructed. The model included multiple objective functions such as operating cost, renewable energy utilization rate and penetration rate, and comprehensive voltage deviation index. A three-layer nested solution framework based on hierarchical sequential optimization was designed, in which constraints were imposed layer by layer to search for the optimal solution set, enabling gradual reduction of the solution space and ensuring the convergence rate and computational efficiency of the algorithm. Experimental results showed that, compared with the pre-optimization case, the daily operating cost of the system was reduced by 44.9%, the renewable energy utilization rate was increased to 98.5%, and the comprehensive voltage deviation index was reduced to 1.8 p.u. after APSA optimization. Compared with commonly used particle swarm optimization algorithms and genetic algorithms, APSA exhibits significant advantages in solution stability and convergence accuracy, and it effectively solves the collaborative optimization problem of source-grid-load-storage for coal mine microgrids, providing an effective solution for safe, green, and economical operation of mining areas.
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