Integration of Bi-Level Model and Mixed Integer Linear Programming for Optimization of Electric Vehicle Charging Stations with Distributed Energy Sources

Abstract

<div class="section abstract"><div class="htmlview paragraph">In this research paper, a novel bi-level approach has been introduced to enhance grid flexibility through a flexible power management system, taking into account the availability of renewable and adaptable resources. The proposed optimization strategy focuses on minimizing the total daily idle time of Electric Vehicles (EVs) by optimizing charging processes at both Fast Charging Station (FCSs) and user-level charging. The objectives of FCS energy management and EV idle time are considered as lower and upper-level models, respectively, which are optimized by the proposed bi-level strategy with Particle Swarm Optimization (PSO) algorithm. The investigation confirms the effectiveness and reliability of the recommended optimization strategy. Test results highlight its success in enhancing financial gains for charging stations and EV users, benefiting grid operators and consumers alike. The outcomes reveal a notable decrease in the FCS day-to-day charge rate, dropping from $3795.84 to $3523.84, marking a 6.34% reduction and providing an advantage to station owners.</div></div>