Research On Distributed Generation Planning Of Distribution Network Based On Improved Whale Algorithm

With the continuous development of China from fossil energy supply system to clean energy supply system,environmentally friendly,energy-saving and efficient small-scale distributed generation(DG)has been favored and strongly supported by the state.The rapid development of DG provides a new idea for distribution network planning.However,the access of DG has two sides.The introduction of DG into the distribution network can reduce the transmission power consumption,enhance the reliability of the distribution network,and improve the efficiency;the grid connection of a large number of DG will also cause obvious fluctuations in the voltage stability of the distribution network.Therefore,based on the influence of voltage fluctuation,sensitivity of relay protection,power flow change and network loss caused by DG grid connection,this paper puts forward the planning scheme of DG location and capacity.This paper describes the impact of DG grid connection on the distribution network.According to the current load level of the distribution network and the total load of long-term planning,the maximum capacity of DG grid connection is determined.By creating a multi-objective planning model including network loss,power quality and economy,the number of DG,single capacity and specific address of grid connection are determined.The selection and sizing of access point of DG are regarded as a problem.The optimization problem of seeking the solution of multi-objective function.The intelligent optimization algorithm used in this paper is based on the WOA.In view of the shortcomings of WOA,such as the lack of far away from local optimization and slow convergence rate,firstly,combined with the idea of self-adaptive inertia weight guiding population optimization in particle swarm optimization algorithm,an adaptive inertia weight adjustment strategy based on sine function is proposed to speed up the convergence speed and improve the performance of the algorithm.Secondly,the random difference mutation strategy is added to improve the local optimum and premature convergence.Finally,the IEEE33 system is used for simulation,and BWOA is compared with GA and PSO.The results show that the objective function of the improved whale algorithm is the smallest in the multi-objective planning model composed of network loss,voltage deviation rate and DG investment cost,which verifies the superiority of the BWOA.