Improved Particle Swarm Optimization Algorithm For Distribution Networks With Distributed Power Sources Research On Reactive Power Optimization

With the changing global energy supply-demand landscape and the trend towards China’s "dual-carbon" goals,distributed generation(DG),such as photovoltaic and wind power,has rapidly emerged as a pivotal player in distribution networks,playing an increasingly important role.The integration of DG into distribution networks not only changes the flow distribution but also alters the operational mode and existing control methods of the networks.Unlike conventional generators,DG exhibits continuous and smooth power output but possesses significant intermittency and volatility,posing challenges for reactive power optimization in DG-integrated distribution networks.It holds significant research value to leverage the reactive power regulation capability of DG in conjunction with traditional control approaches for reactive power optimization.Therefore,this paper focuses on the reactive power optimization problem in DG-integrated distribution networks using an improved particle swarm optimization(PSO)algorithm.The main contributions of this study are as follows:(1)Several common types of DG,including photovoltaic and wind power,are analyzed,and the equivalent nodes in the distribution network are identified.Corresponding models are established,and a forward-backward sweep method is employed to develop a forwardbackward sweep program for DG-integrated distribution networks.By utilizing the IEEE 33-bus standard test system,the impact of DG integration on the distribution network is analyzed.Simulation results demonstrate that the type,location,and capacity of DG integration yield different effects on the power flow in the distribution network.(2)The basic concepts,implementation steps,and pros and cons of the standard particle swarm optimization(PSO)algorithm are introduced and analyzed.An improvement is made by incorporating position variance in the early stage of the algorithm,enhancing the quality of the initialized population,and improving the search efficiency to enable the algorithm to escape local optima and seek global optimum solutions more effectively.(3)Reactive power regulation measures in the distribution network are analyzed,and a multi-objective reactive power optimization model is established with the objectives of minimizing network losses and total voltage deviation.Both the standard PSO algorithm and the improved PSO algorithm are applied for simulation on an enhanced IEEE 33-bus model with DG integration.Simulation results validate the accuracy of the proposed DG-integrated distribution network reactive power optimization model and the effectiveness of the improved PSO algorithm.