A Novel Grid-Forming Inverter Control Strategy for Resilient Operations in an Islanded Microgrid With Bidirectional Electric Vehicle Integration

This paper conducts a detailed analysis of the design, control, and performance evaluation of a 7-bus islanded microgrid system, featuring two Distributed Energy Resources (DERs) units consisting of Solar PV with Battery Energy Storage Systems (BESS), along with a Diesel Generator (DIG) as a third energy source. An Electric Vehicle (EV) is integrated into one of the buses, operating in both Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) modes. The microgrid's control framework is centered around three grid-forming three-phase half-bridge inverters connected to the DER units and DIG. An enhanced droop control method with virtual impedance and a feed-forward derivative mitigates distortions, reduces circulating currents, and improves transient response, enhancing stability and dynamic performance. A Leader-Follower configuration manages the secondary control among inverters, while a Phase-Locked Loop (PLL)-based system ensures synchronization during plug-and-play events of DIG and DER outages. The control approach employs Proportional-Resonant (PR) controllers in a stationary reference frame, delivering high resonant frequency gain, minimal steady-state error, and streamlined implementation without dq transformations. The microgrid, tested in MATLAB Simulink and OPAL-RT environments under various conditions, such as changing solar irradiation, abrupt load shifts, DER failures, and DIG plug-and-play scenarios, demonstrated robustness and efficiency, with voltage and frequency deviations constrained within <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 5\%$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 0.25$</tex-math></inline-formula> Hz, validating the proposed control strategies for autonomous operation.