In recent years,the shortage of energy resources and the problem of environment are becoming increasingly serious.Compared to the traditional centralized power supply,the distributed generation has aroused people's wide attention which has the advantage of clean,efficient and flexible.The generation model that traditional power generation and distributed generation combined with each other has been recognized as the inevitable trend of the future's development of power system.Therefore,the reasonable planning of distributed power supply system in the distribution network system will be an important part of power system planning.The results will directly affect the reliability,stability and power supply quality of the distribution network system.Therefore,it has great theoretical and practical significance to study the optimal allocation of distributed generation in distribution network in order to improve the absorbent capacity of the distribution network,enhance the reliability of the system,and optimize the system operation.The issue of distribution network planning with distributed power supply was turned to a multi-objective optimization problem,and this paper focus on the research and improvement of the two aspects:the objective function and the solving methods.Rational planning of grid connected position and configuration capacity of distributed power supply can ensure better economic and technical utility.On the basis of analyzing the characteristics of DG and the processing method of different types of DG grid connected nodes,considering the factors such as economic,technology and system stability,multi-objective optimal allocation model was established which have the advantages of minimum active network loss,smallest total investment and running cost of distributed power supply and minimum load node voltage deviation.In the aspect of solving method,multi-objective particle swarm optimization algorithm is studied to multi-objective distribution network planning prolems.As to the shortcoming of Particle swarm optimization algorithm's falling into local extreme points,the strategy of inertia weight,dynamic adjustment of acceleration factor and overall situation disturbance are acceded to the solving method.The ability of global exploration,local exploration and the population diversity are enhanced.In order to improve the sorting speed of non-dominated solutions,the diversity and distribution of the Pareto frontier,fast non dominated crowding distance sorting strategy is improved by the adoption of calculation method of uniform crowding distance.In order to achieve the particle's returning to the feasible space within the search which in the premise of not changing the direction of the particle search,dynamic mutation strategy to the cross particle are used.So as to improve the overall situation searching ability of the algorithm.Finally,the simulation analysis in the standard IEEE33 bus distribution network test system.Using the NSGA-II and IMOPSO algorithms to solve the multi-objective optimization problems of distribution network with distributed generation.The superiority and effectiveness of this algorithm is verified by comparing and analyzing the results.Choosing an optimized configuration scheme of distributed power from the Pareto front solutions and comparing random scheme with the optimized configuration scheme to highlight the advantages of the optimized scheme. |