Robust Dynamic and Algebraic State Estimation for Microgrids: A Generalized Approach

Abstract Network control, optimization, and security analysis are facilitated by accurate microgrid state estimation. By utilizing phasor measurement units (PMUs), a combined robust centralized dynamic algebraic approach is proposed in this paper for estimating algebraic states (voltage phasors) as well as dynamic states (associated with synchronous generators and wind turbines). Assuming that a load is placed on each bus, an innovative PMU placement method is also presented to provide measurements for all dynamic and algebraic state variables. As a robust link between algebraic state estimation and dynamic state estimation, the output results of the least absolute value (LAV) estimator, which is robust against bad data, are fed to dynamic state estimators as pseudo measurements. Next, to address the nonlinearity of synchronous generator and wind turbine models, an unscented Kalman filter (UKF) is applied to estimate dynamic states precisely. The numerical tests on a microgrid test system show that the suggested approach is suitable for both algebraic and dynamic state estimation. Synchronous generators and wind turbines are modeled using nonlinear models of the 9th and third orders, respectively, and static loads are modeled as voltage‐frequency dependent ones.