Power System Outlier Detection Based on Improved EKF Algorithm

The impact of outliers on power system state estimation cannot be ignored. These outliers are usually caused by aging system equipment, sensor failures, line connection errors, and so on. In this paper, we propose the use of the Weighted Expanded Kalman Filter (WEKF) algorithm based on projection statistics (PS). The algorithm first uses the projection statistics algorithm to detect outliers in the time-varying detection matrix, and subsequently introduces a weighting function to reduce the weight of these outliers, thereby effectively minimizing the impact on the state estimation. Simulation experiments on the IEEE 14-bus system, the results of the study show that the PS-based Weighted Extended Kalman Filter (WEKF) algorithm exhibits stronger robustness compared to the traditional EKF algorithm. Through the use of the algorithm, it is possible to have the more stable estimation of the state of the power system.