Study On Coordinated Charging Of EV And Energy Efficiency Of EV Charging Facilties

Electric vehicle has entered a rapid development period, disorderly charging brought great impact to the grid.This paper conducts research on coordinated charging of EV relies on actual research project. Firstly, we study load forecasting of EV.On the based of load forecasting factors premise, we classified the use of EV into stationary and random charging type. To study load forecasting of stationary use by cluster analysis method. To study load forecasting of random use by Monte Carlo method. Example shows that the proposed method has a certain accuracy. Combining load forecasting method, we propose to guide and control coordinated charging strategy based on the price of charging. In order to guide, we proposed TOU pricing model and partitioning priceing model. Combined with the charging price elasticity matrix,we use TOU price and partition price to guide charging behaviors of the user in time and space. In order to control we proposed control strategies based on TOU price.We take the coordinated control strategies to minimizing the cost of user charging. Simulation examples show that this strategy can reduce some extent of load fluctuations, reduce the difference of peak and valley load, and "load shifting" effect is more pronounced when large-scale electric vehicles access to grid.With the rapid development of EV, people also begin to pay close attention to the energy efficiency problem of charging facilities and swapping facilities. In the end of this paper, the energy efficiency assessment study of charging facilities and swapping facilities were carried out. The indexes of energy efficiency assessment were put forward combined with the research of influence factors of energy efficiency. The energy efficiency assessment system was built based on fuzzy comprehensive assessment method. The hierarchical comprehensive method was adopted to evaluate the energy efficiency of charging and swapping network. According to the example of simulation, this assessment system can better reflect the energy efficiency level of EV charging and swapping facilities.