Improving Microgrid Short-Term Stability via Model-Predictive Control-Based Setpoint Adjustment

Abstract

A model-predictive controller (MPC) for synchronous generator-based microgrids is introduced to enhance voltage, frequency, and transient stability in fast timescales. The centralized controller uses mathematical models of power system dynamics to predict the evolution of system states over a finite horizon based on information from local state observers and relays. The MPC dynamically adjusts the setpoints of existing primary controls to maximize system stability. To address the computational challenges of a real-time MPC implementation due to nonlinear power system dynamics and short sampling intervals, a trajectory linearization technique is applied to the MPC formulation. The proposed controller is validated on a notional industrial microgrid for a variety of disturbances.