The Research Of Dynamic State Estimation Algorithm In Power System Based On Hybrid Measurements Of WAMS/SCADA

The power system state estimation gives system real-time status for power system's analysis and control. Both the analysis's veracity and control's effect are influenced by the performance of the state estimation. dynamic state estimate (DSE) demonstrate it superior to static state estimates in numerous characteristics. With the aid of an efficient DSE, a system operator can be allowed more time in making control decisions, such as economic dispatch, security assessment, or other related functions. The traditional state estimation only the measurements of the SCADA system. The PMU-phasor measurement unit has been placed in the power system expansively, and the PMU measurements have become another important data source. The PMU measurements have high precision, synchronous sampling, and short updating cycle, and can measure the node state directly. For too high cost for PMU placement, the network is not observable only with PMU. The question how to utilize the PMU measurements in the DSE effectively, must be faced and solved now. The chief research work of the thesis is as follows:(1) This paper make a overall discussion of basic principle and algorithm of dynamic state estimation, and introduce simply the several kinds of typical improvement methods, and show their disadvantage.(2) With the advantage of the WAMS, the status quo on power system state estimation based on WAMS is reviewed and analyzed from three aspects, including the models of using nodal voltage phasor measurements with high accuracy, models of using branch current phasor measurements with high accuracy and models of using all phasor measurements. This paper studies two representative models detail, comments on their advantages and disadvantages.(3) The measurements of WAMS system and SCADA system are both available in the power system, a linear dynamic state estimation algorithm is proposed to deal with this problem in this paper. The measurements of the active & reactive power flow and power injections at nodes of the SCADA system are transformed to the equivalent current phasor by measurement transformation, so that these measurements can be combined with measurements of WAMS and form a mixed measurement system. The proposed algorithm is denoted in rectangular coordinates. In this algorithm, the linear exponential smoothing technique and linear time-invariant Kalman filtering method are used to implement the forecasting and the estimation. Since the proposed algorithm has a constant Jacobian matrix, the calculating time can be significantly reduced, while the calculating precision can also be guaranteed.