The Application Of PMU In State Estimation Of Power System

State estimation provides the real time operational state of the power system. It is the most important part of EMS, and it is the basic of the safety of the system. The conventional state estimation which bases on SCADA has some disadvantages such as low accuracy, poor synchronization and so on. With the development of technology, the WAMS system which bases on GPS technology and PMU placements is more and more mature. So that state estimation has got more opportunities. Considering about the cost and technology, it is not possible to place PMU placement at every bus. Thus WAMS and SCADA will exit at the same time in the future for a long time. Aiming at some questions of WAMS and SCADA hybrid state estimation, this paper makes deep studies about the state estimation algorithm and placement ways.No matter the SCADA or the WAMS system, the algorithms are all base on the conventional algorithm. So, first of all, this paper describes three conventional algorithms of state estimation and simulates the WLS algorithm.Aiming at the WAMS and SCADA hybrid data, this paper establishes a two stage algorithm. In the first stage, the conventional weighted least square estimation is run using supervisory control and data acquisition measurements, and, in the second stage, voltage and current phasor measurements from phasor measurement units are utilized to enhance the output of the conventional WLS estimator. This model maximizes the use of PMU data and will not change the structure of the conventional state estimator will require almost the same computational time.This paper presents a new method for an optimal placement of PMU in hybrid measurement system. PMU has a characteristic that the measurement accuracy of a bus which was placed with a PMU is higher than a bus without PMU. At the same time, the accuracy of state estimation of other buses is influenced by the PMU. And this influence is more obvious if the electrical distance of the two buses is close. Obviously, the influence is week when the two buses are far away. Based on the characteristic, we can put these buses which have closer electrical distance into area, and put one PMU in this area thus every bus in this area is influenced by PMU. First of all, we establish an electrical distance based on the phase angle-active power sensitivity method. Because the number of PMU is knew and the buses in the electrical system are connected with each other closely, so this paper divides the bus nodes in some areas by using the fussy c-means technique. Finally place the PMU on the bus which has the biggest estimation residuals.Finally, this paper simulated the model in IEEE30 node system by MATLAB. The results of data are analyzed and compared, which shows the model is effective and optimize the filtering effect to some extent.