Research Of State Estimation Based On PMU

With the development of power industry, the configuration and operation condition of power system are getting more and more complicated. In order to keep smooth running, the accuracy and completeness requirements of the system real-time status are increasing. As a core function of energy management system(EMS),power system state estimation is able to use the redundant measurements to modify error information caused by random disturbance, enhance measurement data reliability, forecast system operation state, and provide data base for online calculation and analysis applications of power grid.The measurement of traditional state estimation is acquired by supervisory control and data acquisition(SCADA) system, including branch load flow, injection power and nodal voltage amplitude. In the early 20 th century with the development of science and technology, synchronized measurement technique based on global positioning system(GPS) had rapidly risen, bringing high precision and synchronized measurement information of the entire network for state estimation.It has created a new opportunity to enhance state estimation.For the long-term coexistence of SCADA and PMU, firstly the theory of power system state estimation is briefly introduced in this paper, including mathematical models, classic algorithms, and the data matching problems. And some feasible treatment schemes are put forward. Then a new hybrid algorithm is proposed,introducing synchronous measurements to traditional nonlinear state estimation models. This method estimates PMU unobservable states and PMU observable states separately. When compared with conventional approaches, it features reduced computational complexity and greater numerical stability. Finally it is verified by simulation on standard IEEE test systems that this method has more advantages than weighed least square algorithm and fast decomposition algorithm.