Branch Load Data Anomaly Detection Based on State Estimation

To address the quality of branch load data within electricity customers, we propose a state estimation-based method for anomaly detection of branch load data. We perform steady state estimation of the system based on Newton-Raphson Analysis and WLS State Estimation, and then use cardinality tests for grid anomaly data. We use the IEEE14 bus system to simulate the branch load within the customer. The results show that the algorithm can effectively detect anomaly data.