A Holistic State Estimation Framework for Active Distribution Network with Battery Energy Storage System

Battery energy storage systems (BESSs) are expected to play a crucial role in the operation and control of active distribution networks (ADNs). In this paper, holistic state estimation framework is developed for ADNs with BESSs integrated. A dynamic equivalent model BESS developed, transition measurement equations derived. Based on equivalence between correction stage iterated extended Kalman filter (IEKF) weighted least squares (WLS) regression, proposed capture static variables BESSs, especially charge (SOC). bad data processing method also presented. The simulation results show that improves accuracy as well capability detection both providing comprehensive situational awareness whole system.