Nowadays, the world is moving towards green energy vehicles and electric vehicles (EVs) are one of the chosen solutions. Vehicle-to-grid (V2G) technology is gradually gaining attention to support issues of performance optimization, energy fluctuations, reducing grid operating costs and bringing optimal efficiency to owners. Along with the rapid increase in the number of EVs, the deployment of effective electric vehicle charging station (EVCS) infrastructure is desirable. However, improper installation can cause many negative impacts on the grid and vice versa, especially EVCS applying V2G charging and discharging techniques. In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. The solution results are simulated on a 33-node IEEE standard distribution network using Matlab software and compared with the original FA algorithm to evaluate and propose computational solutions to develop the EVCS system infrastructure in practice.