Increasing penetration levels of renewable energy sources in electrical grid distribution systems causes raped power variations drawing from the penetration levels variation in electrical vehicle charging creates the problem in the unity grid. In this paper a new artificial intelligence control technique is introduced in electrical vehicles in order to reduce the power variations caused by the solar power and high low demand. The fluctuations in electrical vehicle scheduling with energy storage has been studied the main effort is the minimizing of power variations in slack bus from the specified value and high utilization storage capability. Energy forecasting and renewable power generation are major considerations in electrical vehicle scheduling. The fuzzy technique is used to define power storage rate of electrical vehicles. Buttery life time was taken as key aspect and parameters that cause buttery degradation are considered while prioritizing PEVs for grid support. However, primary purpose of PEV (to travel) is given highest priority by ensuring maximum energy level before starting a trip.