Research On Static Parameter Detection And Identification Of Power Grid Branch Based On PMU Measurement

Presently,power industry is developing rapidly and the scale of power grid is expanding greatly,making it hard for power grid dispatching operation.And the requirements for reliability and accuracy of the EMS software analysis and decision-making are also getting higher.The accuracy of power grid branch parameters directly determines the effects of EMS analysis and application software of power dispatch control center,and also greatly affects the accuracy and reliability of power dispatching control system.The main reason leading to the inaccuracy of network parameters is that power systems are growing and expanding too fast,which makes it hard for the power grid companies to master the parameters,which are usually replaced by design parameters or estimated parameters.To make it worse,other factors like transmission line reconstruction and changes in operating environment will decrease the accuracy of branch parameters.The following analysis and decision-making software will be harmed,and even the safe and stable operation of power system will be endangered.Presently,with the wide coverage of the WAMS in power system,it is possible to detect the static parameters of power grid branch with PMU measurement.Because of the high synchronization accuracy of PMU sampling,fast data acquisition and transmission,and phase measurement included,it can greatly improve the speed and accuracy of power system parameter detection and identification.The paper presents a method,that is,by the reformation of state space and static state estimation.To improve redundancy,KCL equations are added to the measurement equation which is presented in parameter space.And suspicious parameter detection can be achieved.Then local area can be formed for each suspicious parameter.Linear state estimation or extended state estimation is chosen according to the specific area which contains three winding transformer or not.By the combination of suspicious parameter detection and local identification,combined with statistical analysis of measurement profiles,the adverse effects of lacking precision PMU measurements can be minimized.And error parameters can be identified and the proposed correction values are given.Finally,an IEEE standard test system and a practical example are presented to illustrate the effectiveness of the proposed algorithm.