Smart charging of plug-in electric vehicle using gravitational search algorithm

The conventional views of the power system have been changed by the concept of smart grid and one of the main issues in smart grid is electric transportation vehicles. Recently, the penetration of plug-in electric vehicles (PHEV) keeps growing up. On the other hand, power systems contained PHEVs would probably make increased system peaks and over loading of power system assets if they do not have proper control on charging and discharging of PHEVs. It means that a suitable charging and discharging schedule can avoid overloading of a network at the peak hours by charging on the off peak hours. Since the simulation parameters such as battery capacity, one-way commuting distance and departure time from home and arrival time to home are random, it is necessary to achieve a comprehensive probabilistic mathematic model of PHEVs charging. This paper presents a methodology for modeling the load demand of PHEVs. This model includes some significant parameters such as battery size, charging rate and speed of vehicles. Moreover in this model, we assume some scenario for trips of PHEVs. Furthermore we use an algorithm based on binary gravitational search algorithm (BGSA) for planning the PHEVs´ charging. The model and purposed algorithm have been simulated in MATLAB software and results offer a model of load demand of PHEVs. Also results show the positive effect of smart charging algorithm for the load peak shaving.