Power network maintenance optimization strategy based on elite genetic algorithm

Aiming at the problem of peaking and valley difference of grid load and high charging cost caused by large-scale electric vehicle charging in the process of connecting to the grid, this paper aims to reduce the fluctuation of grid load, relieve the distribution pressure of the grid and reduce the charging cost, build a charging optimization model, design an elite genetic algorithm, and apply it to the optimization of unordered charging, and verify the optimization performance of the proposed algorithm. It provides a strong basis for promoting the vigorous development of the electric vehicle industry. The simulation results show that compared with unordered charging, the elite genetic algorithm can restrain the load volatility of the power grid, and the peak-valley difference rate of the elite genetic algorithm optimized charging mode is 56.38%, which is 26.21% lower than that of unordered charging. From the effect, it can be seen that the algorithm can improve the load curve of electric automobiles.