State Estimation And Optimization Of Distribution Network Based On PMU

With the development of society,people have stricter requirements on the safety and reliability of the power system.State estimation can use advanced measurement to determine the operating status of the power grid in real time and effectively,so as to obtain the safety and stability of the power grid,therefore widely used in power systems.The research of GPS-based phasor measurement unit(PMU)can provide measurement of voltage and current,which is essential for the implementation of the Wide Area Measurement System(WAMS)and also for the realization of the online analysis and monitoring.PMU has been widely employed in power system.Smart grid requires distribution system to be fully controllable,observable and measurable.In general,the more measurement installed,the more accurate the data is.However,considering the economy,it is not realistic to install PMUs on all nodes,so the optimal configuration of PMUs becomes especially necessary.This paper is oriented to distributed network based on PMU,where weighted least square method is the main method.Iterative format of state estimation algorithm for distribution network with node voltage and branch current as state quantities are studied.The derivation of Jacobian matrix and state quantity correction matrix is completed,and comparison between the two methods is finalized.For optimal PMU assessment,state estimate accuracy and the installation cost are considered,combining with genetic algorithms and simulated annealing algorithm to optimize the PMU configuration.The combination of two methods manages to improve the convergence speed of the algorithm,solve the problem that it is easy to fall into a local optimal solution,and obtain a sufficiently high state estimate precision on the premise of installing as few PMUs as possible.