Research On The Effect Of Voltage Caused By Distributed Generation And Optimal Allocation Of Distributed Generation

With the development of the smart grid and sustainable development society,the distributed generation has attracted more and more attention for its environmental, efficient, flexible, and less investment characteristics. The combination of distributed generation and power grid is considered to be the main development direction of the electric power industry in the21st century. The connection of distributed generation to distribution network can reduce environmental pollution,save investment,improve power quality, increase the reliability of power supply,and so on.But it can also bring some negative effects. So,this paper analyses and studies the optimal allocation of distributed generation form the view of reducing the distribution network loss,improving the distribution network voltage quality and improving the distribution network voltage stability margin.This paper firstly introduces the principle,characteristics of technique and application of several major distributed generations.Then,it emphatically analyses and concludes the effect of voltage profile and voltage stability considering three factors:the interconnected location,injected capacity and power factor.The conclusion shows that the rational allocation of distributed generation in distribution network can give full play to the advantages of distributed generation and restrain the negative effects brought by distributed generation.Based on the former analyses,a multi-objective programming model,which takes into account the least active power loss,the best voltage level and the biggest static voltage stability margin,is firstly established.In order to handle the multi-objective optimization which is conflicting and has different dimensions, we use the fuzzy set theory to transform the multi-objective optimization to mono-objective optimization. It maximizes the overall degree of satisfaction to improve the whole performance. In allusion to the premature problem of particle swarm optimization algorithm,we use the adaptive mutation particle swarm optimization algorithm to solve this model.This algorithm introduces mutation opration during the process of optimization.So,it can vary the global extremal and increase the diversity of population when it gets into the local optimal solution.It can avoid the premature convergence problem effectively. At last,simulation is carried on the IEEE33distribution network.The result shows the correctness of model and algorithm which are used in this paper. Through comparative analyses with the result of mono-objective optimization,it proves the multi-objective fuzzy optimization has better overall degree of satisfaction. The model can obtain better economic efficiency while enhance system security and also improve the voltage quality of distribution network.At the same time, through the comparison analysis on the particle swarm optimization algorithm and adaptive mutation particle swarm optimization algorithm,the result proves that the adaptive mutation particle swarm optimization algorithm can overcome the premature convergence problem and it has a better result of optimation than the particle swarm optimization algorithm.