Variable parameter Kalman filter based dynamic harmonic state estimation for power systems with wind energy integration

In order to improve the accuracy of harmonic state estimation in power systems with wind energy integration, a variable parameter Kalman filter model based on historical harmonic information is proposed. In this model, the high frequency and the low frequency components of the historical harmonic wave is obtained through the wavelet filter. The Low-frequency component of historical harmonic is used to calculate the state transition matrix, and then a variable parameter Kalman filter algorithm is adopted to solve the model. The numerical experiment executed on the IEEE13-bus system showed that the proposed method improved the accuracy of the state estimation in the power systems with wind energy integration compared with the classical Kalman filter method.