Application of Enhanced Self-Adaptive Virtual Inertia Control for Efficient Frequency Control of Renewable Energy-Based Microgrid System Integrated With Electric Vehicles

Abstract

The frequency control of an islanded microgrid (MG) is a challenging task due to the lack of system inertia as it is highly penetrated with renewable energy sources (RESs). Current work suggests overcoming this issue with an energy storage system (ESS)-based virtual inertia (VI) approach by providing appropriate proportional damping instead of a fixed value. In this study to overcome the frequency control issue, a fuzzy-based self-adaptive enhanced VI controller (SAEVIC) coordinated with electric vehicles (EV) is proposed. The controller is proposed to stabilize the system frequency and balance state of charge (SOC) of plugged-in electric vehicles (EVs). The performance of the proposed controller is justified in terms of frequency control over with/without conventional VI control, conventional enhanced VI control, and self-adaptive VI control. The system frequency and SOC signal are considered for the control action of the proposed controller. The impact of EV integration on the system frequency dynamics is tested. The validation of the proposed controller is carried out with a system injected with stochastic disturbances, high and low levels of renewable energies, denial of service attacks on renewable energy, and disturbed operating conditions with varied internal parameters. It is noticed that with the SAEVIC approach, the overshoot (OS)-11.40%, undershoot (US)- 46.46%, settling time (ST)-98.6% and fitness value-10.27% are decreased as compared to conventional enhanced VI approach under Stochastic variations of wind, PV, and multi-step load disturbance of MG system.