Reactive Power Optimization Model for Port Shore Power Based on Mayfly Algorithm

This paper proposes an optimization strategy for the integrated “ship-shore-grid” collaborative energy supply network architecture based on an improved mayfly algorithm, aiming to address the reactive power optimization problem in port power grids. By introducing Chebyshev chaotic mapping and cosine function-based nonlinear weights, the improved mayfly algorithm enhances global search capabilities, avoids local optima, and accelerates convergence speed. Applied to the reactive power optimization of port-area power grids, the algorithm effectively reduces system power losses and improves voltage stability. Simulation results demonstrate that the improved mayfly algorithm outperforms the standard mayfly algorithm in both optimization effectiveness and convergence speed, significantly enhancing the operational efficiency and economic performance of port-area power grids integrated with distributed renewable energy and shore power loads.