Research On Large Scale Of Electric Vehicle Coordinated Charging Strategy

With the breakthrough of electric vehicle technology, promotion of national policy, change of consumption concept of electric car users, the development of electric vehicles must be scale in the future. But the space and time characteristic of the electric car charging is uncertain. A large amount of electric vehicles disordered charging will bring a load growth to the power grid, increase the difficulty of power operation control, reduce the power quality. Study of large scale of electric vehicle coordinated charging control strategy has important theoretical and practical significance.This thesis studied layer zone control method based on virtual control charging station center, the order charging control strategy response by the user is proposed. The main researches and works are summarized as follows:(1) The research on EV charging characteristics are analyzed from charging mode and EV species.. It studied the EV charging time model, spatial and power characteristics. And it used Monte Carlo method to simulate large-scale EV impact on power grid. With A city as an example, the disordered charge on different developmental stages of the electric vehicles was simulated. Results show that it caused power grid load curve fluctuates significantly, increased the peak valley difference, and formed two peaks.(2)The method of the virtual charging station as control center is put forward. The users can response peak valley prices independently. The strategy set users spent at least and minimum peak valley difference as objective function. And optimized genetic algorithm is used to solve the problem. With a charging station as an example, which is simulated by Matlab. And the results indicate that without considering the need for electric vehicles,90%of users to response the strategy can effectively cut the peak to compensate the valley. And it can arrange electric car in low hours to charge, which can reduce the user charge fees. While20%of users to response the strategy can’t make obvious effect.(3)Based on different response to the strategy of users, factors of the user response to the peak valley price are analysis, which are price, period of time and demand of users. It set up the model of user behavior response to peak valley electricity pricing,the response of use behavior to the peak and valley period is studied. It used membership function divides the peak time. The strategy set users spent at least and minimum peak valley difference as objective function. Optimization algorithm is used to determine the price. Take A city in2030as an example,the simulation results show that after optimization of price and time, on the basis of meeting electric vehicle users on the use of vehicles, it can make user to response to the orderly charge control strategy in maximum proportion, enable users to response the peak power better, enhance economic benefits and have more practical significance.