Model Predictive Frequency Control of Low Inertia Microgrids

In isolated power systems with low rotational inertia, fast-frequency control strategies are required to maintain frequency stability. Furthermore, with limited resources in such isolated systems, the deployed control strategies have to provide the flexibility to handle operational constraints so the controller is optimal from a technical as well as an economical point-of-view. In this paper, a model predictive control (MPC) approach is proposed to maintain the frequency stability of these low inertia power systems, such as microgrids. Given a predictive model of the system, MPC computes control actions by recursively solving a finite-horizon, online optimization problem that satisfies peak power output and ramp-rate constraints. MATLAB/Simulink based simulations show the effectiveness of the controller to reduce frequency deviations and the rate-of-change-of-frequency (ROCOF) of the system. By proper selection of controller parameters, desired performance can be achieved while respecting the physical constraints on inverter peak power and/or ramp-rates.