Research on structural design and stability improvement of new power system energy storage network based on optimization algorithm

In the process of constructing a new type of power system, energy storage configuration plays an important role in supporting the stable operation of a new type of power system mainly based on new energy.This paper constructs an optimization model with the constraints and optimization objectives of the optimal configuration of the new power system.The improved MOPSO algorithm is proposed to be written in Matlab language for model solving.The standard test functions ZDT1-ZDT4 are selected as test examples to verify the effectiveness and performance advantages of the proposed algorithm.The improved MOPSO algorithm and the typical multi-objective algorithms NSGA-II and MOSPO are evaluated by the multi-objective algorithm evaluation index.The test results show that the improved MOPSO algorithm has the best overall performance, and the Pareto front solution is more uniformly distributed and more diversified.Taking the IEEE-34 node system with wind/light/diesel/storage islanded grid topology selected as an example, the improved MOPSO algorithm is used to design the energy storage network structure and improve the system stability.The optimal access locations of energy storage are found to be nodes 834, 860, and 836, and the multi-storage configuration scheme designed in this paper improves the voltage stability by 77.96%.The research results have important theoretical and engineering value for exploring the optimal configuration scheme of energy storage in distribution networks. Index Terms energy storage configuration, optimization model, MOPSO algorithm, new power systemIn this paper, the constraints of the energy storage system in terms of rated power, rated capacity, charging and discharging power, and charging state are sorted out, and the objectives of economy, reliability, and stability of the optimized energy storage configuration are studied in detail.Aiming at the multi-objective optimization problem of energy storage configuration in new power system, a method of optimizing energy storage configuration in distribution network based on multi-objective particle swarm optimization (MOPSO) algorithm is proposed.The MOPSO algorithm is used to solve the multi-objective energy storage configuration model, and an adaptive mutation strategy is introduced during the population update process to expand the particle's ability to explore the space, which effectively improves the diversity of the population while ensures late convergence, and obtains the globally optimal solution in the energy storage configuration problem.According to the analysis results, the energy storage network structure is redesigned to achieve the best optimal energy storage configuration.