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For the consideration of environmental aspects of the personal transportation, electric vehicle (EV) and plug-in hybrid electric vehicle (PHEV) has the prospective solution nonetheless there is an obstacle to access the charging system plug. Additionally, the charging system delivers its own troubles when we compared it with petrol station since the participation of the different charging alternative. For the last few years, the studies associated with optimization of PHEV/EV charging infrastructure have drawn the researcher׳s consideration. New challenges and chances for the growth of smart grid technologies depend upon the recently introduced electric vehicle charging infrastructure services. In this particular review study, the literature bearing on the use of optimization methods for charging infrastructure is considered. [ABSTRACT FROM AUTHOR]

Recent researches towards the use of green technologies to reduce pollution and higher penetration of renewable energy sources in the transportation sector have been gaining popularity. In this wake, extensive participation of plug-in hybrid electric vehicles (PHEVs) requires adequate charging allocation strategy using a combination of smart grid systems and smart charging infrastructures. Daytime charging stations will be needed for daily usage of PHEVs due to the limited all-electric range. Intelligent energy management is an important issue which has already drawn much attention of researchers. Most of these works require formulation of mathematical models with extensive use of computational intelligence-based optimization techniques to solve many technical problems. In this paper, gravitational search algorithm (GSA) has been applied and compared with another member of swarm family, particle swarm optimization (PSO), considering constraints such as energy price, remaining battery capacity, and remaining charging time. Simulation results obtained for maximizing the highly nonlinear objective function evaluate the performance of both techniques in terms of best fitness. [ABSTRACT FROM AUTHOR]