A controlled electric vehicle charging strategy considering regional wind and PV

Renewable energy, such as wind and PV, produces intermittent and variable power output. When superimposed on the load curve, it transforms the load curve into a `load belt´, i.e. a range. Furthermore, the large scale development of electric vehicle (EV) will also have an significant impact on power grid in general and load characteristics in particular. This paper aims to develop an controlled EV charging strategy to optimize the peak-valley difference of the grid when considering the regional wind and PV power output. The probabilistic model of wind and PV power output was developed. Based on the probabilistic model, the method of assessing the peak-valley difference of the stochastic load curve was put forward; a two-stage peak-valley price model was built for controlled EV charging; on this basis, an optimization model was built, in which genetic algorithms were used to determine the start and end time of the valley price, as well as the peak-valley price. Finally, the effectiveness and rationality of the method is proved by the calculation result of the example.