Distribution Network State Estimation Method Based On Distribution Phasor Measurement Unit(?PMU)

With the continuous improvement of the level of distribution automation system,it is becoming more and more important to improve the power quality of distribution network with rapid and accurate state estimation.At present,most of the state estimation methods are based on the transmission network,but the research on the distribution network state estimation is not mature.Due to its own three-phase imbalance,small X/R ratio,radiation or weak loop network structure,the large measurement data error based on the original distribution network Supervisory Control and Data Acquisition(SCADA)system,the transmission network state estimation can not be implemented simply to the distribution network,and the growing quantity of distribution network measurement at the present stage provides the possibility.to the distribution network state estimation.The traditional distribution network is based on the SCADA system,in recent years,smart meters have been popularized in the distribution network.with the continuous development of Micro-synchronous Phasor Measurement Unit(?PMU),the ?PMU data,Advanced Metering Infrastructure(AMI)data and SCADA data will coexist for a long time in the future distribution network.However,because of the low accuracy of SCADA data,the long sampling period and poor real-time performance of AMI data,and the low overall coverage rate of ?PMU,in the case of the coexistence of three kinds of data,it is difficult to effectively use the mixed measurement based on the ?PMU to estimate the distribution network quickly and accurately.Under this background,the research work is carried out in this paper,the main contents are as follows:The paper summarizes the methods of distribution network state estimation,analyses the advantages,disadvantages and applicability of various methods,describes the development process of ?PMU,concludes the distribution network state estimation considering the ?PMU and AMI measuremen.The paper analyses the characteristics of ?PMU data,compares the difference between ?PMU data and SCADA data,AMI data,summarizes the method of mixed measurement data fusion on the four aspects: data composition,data accuracy,data time section and data refresh frequency,and proposes a hybrid measurement data fusion method based on the current distribution network measurement system.The branch current method can realize the decoupling of the real part,the virtual part,the three-phase decoupling and simplify Jacobian matrix,which greatly improves the operation speed.And it is applicable when the load measurement is accurate in the distribution network.In view of the more accurate load data under the distribution network mixed measurement,the basic method based on the branch current method is adopted,and based on this,a kind of distribution network state estimation method based on ?PMU is proposed.Aiming at the low update frequency of AMI measurement data,AMI sampling and non sampling time are processed respectively,and the Extend Kalman Filter(EKF)is used to effectively use SCADA and ?PMU data to complete real-time tracking of injected node's active power and reactive power,to make up the incoordination of the update period of AMI data,and to improve the accuracy of the mixed measurement,to improve the accuracy of the mixed measurement and the prediction ability of the distribution network overall running trend.Meanwhile,and the bad data and weak loop network are considered in the distribution network to optimize the algorithm,so that it can be more adapted to the distribution network state estimation.MATLAB software is used to verify the effectiveness of the algorithm for the IEEE 13 node and the IEEE 123 node distribution network,and the practicability of the algorithm for the 10 kV distribution line of Jiangxi province.The influence of different measurements,the introduction of the slack node,the bad data and weak loop network on the state estimation and the influence of the two measurement systems on different estimates are compared.It is proved that this method can effectively enhance the accuracy of the state estimation.