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 transportation sector towards global Net-zero target. However, charging/discharging PEVs impacts electricity network’s stability, increases operating costs, and affects voltage profile. This paper proposes a flexible multi-objective optimization approach to evaluate deploy vehicle-to-grid grid-to-vehicle considering techno-economical environmental factors. Furthermore, life cycle PEV batteries, pattern, driving behaviours owners considered. The simulations run over modified IEEE 69-bus radial distribution test system minimize two objective functions including costs CO2 emissions using heuristic-based Firefly Algorithm in stochastic framework renewable generations, load consumption, timing as uncertain parameters. results demonstrate significant reductions emissions, profile network is improved properly. Besides, by implementing discharging facility network, save considerable amount costs.