Optimal integration of electric vehicle charging stations and distributed generator in microgrids using bio-inspired optimization techniques

Abstract

The prompt adoption of Electric Vehicles (EVs) offers substantial challenges to modern power distribution systems, incorporating enlarged power demand, voltage variability, and elevated energy losses. To solve such problems, this paper proposes an integrated optimization scheme for the simultaneous allocation of EV Charging Stations (EVCSs) and Distributed Generators (DGs) within a microgrid. Using the IEEE 33-bus radial distribution network as a test case, an objective problem is expressed for reducing active power loss and voltage variation while increasing the Voltage Stability Index (VSI). The proposed framework is solved using three metaheuristic algorithms: the novel Walrus Optimization Algorithm (WaOA), alongside the well-established Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). Simulations across various scenarios reveal that uncoordinated EVCS integration severely degrades system performance, whereas the optimal co-placement of EVCSs and DGs dramatically enhances operational efficiency. The WaOA consistently demonstrated superior performance, notably in a scenario with three optimally placed DGs, achieving a 53.79% reduction in active power losses (from 202.53 kW to 93.59 kW) and a 50.44% reduction in reactive power losses. In addition, it significantly enhanced the voltage profile, boosted the minimum VSI from 0.6956 to 0.92721, and reduced the lowest voltage deviation to 0.000128 p.u. Comparative study confirms that WaOA outperforms PSO and WOA in both convergence speed and solution quality. This study underscores the critical importance of coordinated planning for EVCS and DG integration, providing a robust strategy to enhance grid reliability and support the sustainable transition to electric mobility.