A fast and robust state estimator based on exponential function for power systems

In realistic power system state estimation, the distribution of measurement noise is usually assumed to be Gaussian while many researcher have verified that it can be non-Gaussian. In this paper, a new robust state estimator based on exponential absolute value function is proposed to address the non-Gaussian measurement noise and outliers. The influence function, a robust statistics tool, is used to obtain the state estimates to reduce its computational burden. A state estimation mean squared error formula of the proposed robust estimator is derived which can be used as a reference in the wide area monitoring system design or upgrade. Simulation results obtained from the IEEE 30-bus, 118-bus and 300-bus systems verify the effectiveness and robustness of the proposed robust estimator.This work was supported in part by the National Natural Science Foundation of China under Grant 61903314; in part by the Basic Research Program of Science and Technology of Shenzhen, China, under Grant JCYJ20190809162807421; and in part by the Natural Science Foundation of Fujian Province under Grant 2019J05020