Modified Differential Evolution Algorithm for Governing Virtual Inertia of an Isolated Microgrid Integrating Electric Vehicles

Abstract

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.