A forward/backward robust state estimation algorithm for radial and simple loop distribution systems

Abstract

The data integration of high voltage (HV) and medium voltage (MV) distribution power grids is a development trend in future energy management systems. This integration brings about challenges such as handling large-scale networks and bad data, which can impact the speed and accuracy of state estimation. To address these issues, a forward/backward sweep (FBS) robust state estimation algorithm (FB-SE) is proposed, particularly suitable for simple loop and radial distribution systems. The algorithm consists of two stages: 1) Bad Data Pre-processing (BDP); and 2) Branch Power Flow State Estimation; Both stages follow the FBS strategy. The preprocessing of bad data only involves one FBS calculation, aiming to identify and rectify obvious bad data; The branch power flow state estimation introduces the weights of state estimation and uses a classification normalized residual index function to achieve weight allocation. The state estimation algorithm proposed in this paper avoids solving Jacobian matrices and linear equations. It can also handle simple ring networks by opening the loop and performing power compensation. The simulation results based on IEEE examples show that this algorithm has advantages in computation speed, robustness, and convergence.