A New Way of Optimal Scheduling of Virtual Energy Storages for Microgrids Regulation

Frequency regulation is a crucial task in autonomous microgrids that demands increased attention. With the advent of stochastic renewable sources and electric vehicles, maintaining frequency in the nominal range has become more complicated. In this article, we propose an optimal approach to utilizing Electric Vehicles (EVs) as virtual storage units via Vehicle 2 Grid (V2G) and Grid 2 Vehicle (G2V) modes. We suggest a multi-objective optimization that includes voltage and frequency regulation as two objectives, providing a range of solutions for the optimal use of EV power in each time interval. In the second stage, we present a smart decision-making strategy to select fleets and EVs for participation in MG support. Three decision-making strategies are implemented using decision trees, fuzzy controllers, and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). The selection process for EVs considers battery degradation as one of the key aspects. Additionally, the analysis of MG energy cost is performed in various cases, accounting for line losses and load factor in the EV selection process. The selection process involves five decision parameters.