Appropriate Tolerance Value Selection of Least Measurement Rejected Algorithm for Robust Power System State Estimation

Abstract

An accurate estimation of a power system’s state is a major requirement in the modern-day power system. An interconnected and highly nonlinear system requires a reliable and efficient algorithm for monitoring of the system’s status in order to have a secure operation. The presence of wrong measurements has made the estimation process a challenging one. An efficient and reliable state estimator should have the ability to detect and eliminate the effects of bad-data during the estimation process. Least Measurement Rejected (LMR) estimator is one of such robust estimators with higher computational efficiency and better reliability. The performance of LMR estimator mainly depends upon the tolerance value of loaded measurements and tolerance is a constant value assigned to each of the measurement. This paper presents an efficient method of tolerance value selection for LMR estimator. Such selection of tolerance value will ensure the robustness of the estimator in terms of estimation accuracy and will provide better computational efficiency. The estimation accuracy and computational time of the proposed approach has been compared with Weighted Least Square (WLS) and Weighted Least Absolute Value (WLAV) estimator. The IEEE 30-bus system has been used to demonstrate the performance of the proposed estimator under different sets of bad measurement (single and multiple) scenarios.