Multi-objective Optimization of Power System Capacity Configuration Using NSGA-II Algorithm

In the modern world, carbon reduction in the power system is the key path for China to achieve the dual-carbon goal. While carbon emission decreasing usually causes the increase of operating cost and electric fluctuation. In order to comprehensively analyze the realization path of the dual-carbon goal of the power system, this paper uses the Monte Carlo method to fully simulate the uncertainty on both sides of the source and load and establishes a power system dispatch model including wind power, solar power, coal power and power storage system. Then, the NSGA-II algorithm is used to optimize the capacity allocation of four types of units with the goals of minimum total carbon emissions, minimum total cost and minimum load fluctuation rate in the whole life cycle power generation, and obtain the multi-objective optimization Pareto front. Finally, the optimal solution is obtained by applying the TOPSIS decision method. Compared with the reference state, the optimal solution can reduce the total carbon emissions of the power system by 5.7%, reduce the total cost by 33.1%, increase the load fluctuation rate by 30.1%, and increase the proportion of new energy generation by 71.7%. The results of this pa-per can provide a reference for the capacity allocation of power system that takes into account low carbon, high economy and high stability at the same time.