Virtual Inertia Emulator-Based Model Predictive Control for Grid Frequency Regulation Considering High Penetration of Inverter-Based Energy Storage System

Abstract

As awareness of human footprint grows, solutions are investigated to reduce greenhouse gas emissions (GHG). To reduce the carbon intensity of electricity production, a massive deployment of renewable energy sources (RESs) has become a mandatory goal. A significant challenge behind the deployment of RESs is the frequency regulation of such systems due to the high penetration of inverters based on energy storage systems (ESS). To overcome this issue, this manuscript proposes, as the main contribution, to use a virtual inertia emulator-based model predictive control. MPC is an optimization-based control strategy that aims at finding the optimal control actions of a system by predicting its future behaviors. This control solution is compared to a proportional (P) and a proportional integrator (PI) controller. The results of this study show that the MPC controller reduce the minimum ESS capacity by 55% and 2%, and the ESS energy throughput by 86% and 36% compared to a P and PI controller. Those results suggest that the MPC controller can help to diminish the CAPEX and ESS aging compared to a P or PI controller.