Multi-Objective Optimal Scheduling of Distribution Networks Based on Multi-Objective Particle Swarm Optimization Algorithm

With the large-scale access of distributed power sources to the distribution network, the complexity of the new power system increases significantly, and the traditional scheduling method is difficult to balance the economy and power supply reliability, so the optimal scheduling of the distribution network has become the key to solve the problem. To address the above problems, this paper proposes an improved multi-objective particle swarm optimization algorithm, which establishes a multiobjective optimal scheduling model for distribution network by considering the uncertainty of photovoltaic and wind power output prediction, combining with the orderly power consumption strategy, and taking the minimization of operation cost as the objective function. Simulation results show that compared with the traditional algorithm, the proposed algorithm reduces the cost by 13.3 %, effectively verifying the feasibility of the scheme.