Data Adjustment of Power System Based on Kalman Filtering and Adaptive Filtering

With the rapid development of the infrastructure in power system, the modern power system possesses a distinctive feature of giant amount of data sets. This causes a serious problem about how to get a better quality of the data gathered from the measurement system. This paper proposed a dynamic system error adjustment method based on the combination of Kalman filter and adaptive filter to focus on the voltage phasor information. The most distinguishing part is that the calculation cost is small and is suitable for on-line computation, which is able to apply during the data transmission and can provide relatively reliable real-time decision foundation for operation and maintenance staff. The combination of adaptive filtering and Kalman filtering shows a better adjustment effect and tracking performance compared to traditional EKF and it is proved using a MATLAB/Simulink simulation of an actual 85-node power system to acquire actual value and measurement value of certain random selected nodes.