Research on Scheduling Strategy of Wind-Solar-Thermal-Storage System Based on MNSGA-II

This paper proposes an improved NSGA-II algorithm (MNSGA-II) to address the issues of local optima and insufficient population diversity in the process of solving economic dispatch strategies for power systems. The algorithm first uses Faure sequences to initialize the population, improving the quality and distribution uniformity of the initial solution; Secondly, design a dual archive maintenance strategy that updates the convergence archive through PBI values, updates the diversity archive through Manhattan distance, and combines truncation mechanism to prevent archive overflow, enhancing the algorithm’s global search capability. In the process of evolution, combining two archive information for environmental selection balances convergence and diversity. The application of MNSGA-II to the power scheduling problem of four generator units shows that compared with traditional NSGA-II and its variants, the algorithm proposed in this paper performs better in terms of optimization accuracy and stability, providing an effective solution for multi-objective optimization of power systems under complex constraints.