Research On Distributed Generation Cluster Division And Optimal Scheduling Technology

Today’s world is facing increasingly prominent problems of ecological environment pollution and fossil energy crisis,and the development of renewable energy is a necessary solution to alleviate the dependence on fossil energy.With the support of various policies in China,the proportion of distributed renewable generation(DRG)in the distribution network is constantly increasing.There are many DRG devices connected to the distribution network,and the installation locations are scattered.The traditional centralized control method faces huge communication pressure,and the uncertainty of DRG output and load will also bring challenges to the economic dispatch of distribution network,which is not conducive to the safe and stable operation of the distribution network.Aiming at the above problems,this paper carried out the research work on distributed power cluster division and distributed power cluster optimal scheduling technology.In terms of distributed power cluster partition indicators,the cluster partition results of commonly used spatial distance index and electrical distance index were compared and analyzed,and a voltage sensitivity cluster partition index was proposed for node voltage control.Considering the operation and management factors of distributed power generation,a distributed photovoltaic cluster partition method based on the grid-connected mode is proposed,which can provide a reference for grid companies to operate and manage photovoltaic clusters.In terms of distributed power cluster partition algorithm,the performance of genetic algorithm,particle swarm optimization and K-means clustering algorithm in cluster partition is compared and analyzed,and a method combining genetic algorithm and K-means is proposed for cluster partition.This method can effectively improve the optimization ability of Kmeans and reduce the optimization time of genetic algorithm.Aiming at the problem of huge communication burden in centralized control of distribution network with high proportion of DRG,an optimal dispatching model of distributed power generation cluster is established based on cluster partition.Applying the alternating direction of multipliers method(ADMM)to the optimal scheduling of distributed power clusters,establishing the optimal power flow model of distributed power clusters,using ADMM for distributed optimization can effectively avoid the huge communication burden faced by centralized control,protect the privacy of information inside the cluster and improve the stability of system operation.On this basis,further considering the economics of cluster operation,the uncertainty of DRG output and load,a robust optimal economic scheduling model for distributed power generation clusters is constructed,and a box-shaped uncertainty set is used to describe the operation scene set considering the uncertainty of DRG and load,and the genetic algorithm is used to search for the scenario with the largest operating cost in the scene set,and then ADMM is used to solve the optimal power flow with the smallest operating cost in this scenario,so as to obtain the day-ahead scheduling scheme of each cluster.The proposed method has good robustness and economy,can effectively deal with the uncertainty of DRG and load.The distributed power cluster partition method and the distributed power cluster optimal scheduling method proposed in this paper have important reference value for the friendly grid connection and optimal scheduling of large-scale distributed renewable energy.