| Distribution network at the end of power system plays a role in dispatching and dispatching electric energy to all kinds of users.It is a key link with the user.Its operation reliability is directly related to the power supply level of the whole power system.The optimal operation of the distribution network can adjust the operation state of the equipment in the system reasonably,and then realize the optimal balance of power supply and consumption.Based on the principle of minimum power purchasing cost,the optimal dispatching of distribution network connected with distributed generation is studied.The research has obtained the ideal effect.This paper describes the research status of distribution network optimization scheduling for distributed generation and distributed generation at home and abroad.This paper introduces wind power,photovoltaic power generation,energy storage and micro gas turbine distributed generation mainly used several types of batteries,and shows the running characteristics of the output characteristics and the various power generation scheduling,distributed power access to distribution network system network loss and voltage distribution are simulated.This paper describes the principle and main operation process of the basic particle swarm optimization algorithm.In order to solve the problem that it is easy to fall into local optimum,an improved immune particle swarm optimization algorithm based on double population learning strategy is proposed based on a strategy of dynamically adjusting learning factor and inertia weight.In this paper,we choose immune concentration and combine double population strategy to increase the diversity of particle swarm,so as to avoid premature convergence.Dynamic adjustment of learning factor and inertia weight ensures the stronger local search ability in the later stage of evolution.The effectiveness of the proposed algorithm is verified by the optimization analysis of three functions.In this paper,the optimal dispatching model of distribution network with distributed generation is established with the objective of minimizing the power purchase cost of power company,and the corresponding constraints in the model are described and the fitness function is constructed.In this paper,an improved immune particle swarm optimization algorithm for distribution network optimization scheduling process is presented.The childhood story is simulated and optimized according to the 10 kV power distribution system of 35 kV power station of Qingzhou power supply company.The results show that the price of the distributed generation restricts its output in the distribution network.With the improvement of the price of the network,it can be more involved in the operation of the distribution network by using the system to improve the cost of the system. |
