Outlier-Resistant Recursive State Estimation for Renewable-Electricity-Generation-Based Microgrids

In this article, a new state estimation (SE) problem is studied for a class of renewable-electricity-generation-based microgrids with measurement outliers. A state-space system model is proposed for microgrids by resorting to the physical laws of power systems where, in accordance with engineering practice, the prior knowledge of the measurement outliers is unavailable. To enhance the insensitivity against measurement outliers, an outlier-resistant SE algorithm is developed with two distinct features: 1) a saturation function is adopted to constrain the innovation term in the state estimator so as to mitigate the negative influences from the outlier-contaminated measuring data; and 2) an upper bound on the estimation error covariance is first ensured and then minimized by selecting proper gain parameters. Finally, simulation studies with three scenarios are carried out on the benchmark of islanded microgrid which contains two renewable-electricity-generation units to illustrate the validity of the developed outlier-resistant SE algorithm.