Multi-Objective Stochastic Techno-Economic-Environmental Optimization of Distribution Networks with G2V and V2G Systems

Plug-in electric vehicles (PEVs) are one of the most promising technologies for decarbonizing the transportation sector towards the global Net-zero target. However, charging/discharging of PEVs impacts the electricity network's stability, increases the operating costs, and affects the voltage profile. This paper proposes a flexible multi-objective optimization approach to evaluate and deploy vehicle-to-grid and grid-to-vehicle technologies considering techno-economical and environmental factors. Furthermore, life cycle of PEV batteries, charging/discharging pattern, and driving behaviours of the PEV owners are considered. The simulations are run over a modified IEEE 69-bus radial distribution test system to minimize two objective functions including the operating costs and CO ₂ emissions using the heuristic-based Firefly Algorithm in a stochastic optimization framework considering renewable generations, load consumption, and charging/discharging timing of PEVs as the uncertain parameters. The results demonstrate significant reductions in the operating costs and CO ₂ emissions, and the voltage profile of the network is improved properly. Besides, by implementing the discharging facility of PEVs in the network, the PEV owners save a considerable amount in operating costs.