A Decision Function Based Smart Charging and Discharging Strategy for Electric Vehicle in Smart Grid

As the number of Electric Vehicle (EV) increases, the uncontrolled EV charging behaviors may cause the grid load fluctuations and other passive effects. In order to balance the EV charging load in the smart grid, an Electric Vehicle Charging and Discharging Strategy (EVCDS) which is based on a Charging Decision Function (CDF) as well as a Discharging Decision Function (DDF) is proposed. In the CDF and DDF, there are three sub-functions related to the residual energy of battery, EV's charging habits, and the charging efficiency of charging station respectively. The residual energy of battery is used to calculate the excepted probability that satisfies the user's mileage requirement, which is an important factor. The charging habits are used to calculate the second sub-function value, which stands for the user's comfort. The charging efficiency and distance are combined together to calculate the third sub-function. All the sub-functions are weighted and combined into the CDF and DDF to decide whether to charge, discharge or do nothing. In the numerical results, we set up a scenario for the commercial vehicles and private vehicles. After compared with other strategies, EVCDS performs well in terms of reducing the charging demand fluctuations and improving the charging demand balance among charging stations.