Study On Partitioned Hierarchical Optimal Regulation Strategy Of Power Quality Devices In Distribution Network Based On MOPSO

With the expansion of the power grid scale,a large number of nonlinear and random loads are distributed into the grid,causing harmonic,reactive power,and other power quality problems become more prominent and coexist.As a result,the distribution network falls into a situation of various power quality problems,lack of strategic decisions,and difficult application.Concurrently,the types of power quality devices are diverse and coupled with each other,but traditional allocation and regulation strategy lacks coordination,which leads to overlapping compensation and low economic benefits.This thesis focuses on the research of harmonic and reactive power integrated optimal allocation and regulation strategy for multi-power quality devices in distribution network,as well as the improvement of dynamic response ability of power quality devices.For the purpose of global power quality compensation,a comprehensive evaluation model of power quality is established using the Analytic Hierarchy Process(AHP)and Relevancy Function(RF).The correlation and difference between each power quality index are fully considered,and on this basis,the objective function corresponding to each power quality index is established based on the effect and benefit.Multi-objective Particle Swarm Optimization(MOPSO)is adopted to the optimization strategy,in which power quality management devices are regarded as compensation resources.A allocation and regulation strategy based on MOPSO is proposed,realizing the compensation for harmonic distortion and reactive power loss within the allowable range of resources.In order to improve the dynamic response ability of power quality devices,a partitioning algorithm based on the combination of Modularity Function(MF)and Fuzzy Clustering Algorithm(FCA)is adopted to reduce the variable dimension in the calculation of allocation and regulation strategy.The complexity of the model is analyzed under the influence of high dimensional parameters from intelligent optimization algorithm in complex network structure.Moreover,MOPSO and Genetic Algorithm(GA)are combined into GA-MOPSO to improve the convergence ability of the algorithm on the basis of the partitioning algorithm.Aiming at the potential time-scale mismatch between power quality fluctuation and control,the hierarchical regulation strategy based on local database and master station is proposed.The above improvements is combined and a strategy for improving dynamic response capability of power quality devices based on Partitioned Hierarchical GA-MOPSO(PHGA-MOPSO)is obtained,which could reduce the amount of computation required by intelligent algorithm iteration effectively and improve the dynamic capability of power quality compensation.Based on the experimental verification of PSCAD/EMTDC and MATLAB/Simu--link simulation platforms,verification of the proposed PHGA-MOPSO regulation strategy is conducted.The harmonic and reactive power integrated optimal allocation and regulation for multi-power quality devices and the dynamic performance of power quality regulation were verified.The experimental results prove the feasibility of the proposed regulation strategy for power quality devices,which testified the effectiveness of the dynamic response capability improvement strategy for power quality devices based on PHGA-MOPSO regulation.There are 52 figures,33 tables and 96 references in this thesis.