Research On Optimal Control Of Large-scale Electric Vehicles Charging And Discharging

With the increase of environmental pollution and energy consumption, the electric vehicle (EV), a kind of clean and environmental transportation, plays an important role in resolution of environmental pollution, energy shortage as well as adjustment of energy structure. Electric vehicle industry has a broad development prospects. The entering of large scale of EVs to the market brings ineluctable impact to power quality and economic operation of the distribution network. Therefore, it is of greatly practical significance to research on the impact of large-scale EVs integration on distribution network, and put forward the corresponding optimization strategies to control and manage the EVs charging load.To make EVs integrated into the power system preferably, this article focus on the research of EVs charging and discharging control.On the study of simulation of EVs charging load, a charging load mode has been built, which considers main influencing factors. Based on the Monte Carlo method, the charging performance of EVs has been stimulated. On the analyzing of impact of EVs charging load on power loss and voltage deviation under different scenarios, the random integration of large-scale EVs would cause the much higher peak load, make the voltage deviation be more obvious with the rising penetration rate of EVs.For a better management of EVs’behavior, a kind of hierarchical control structure has been proposed. Through the EV aggregator agents, a number of EVs were aggregated to participate in the power system dispatching management. Under this control structure, methods for evaluating the impacts of EVs on distribution network under different charging strategies were proposed. The corresponding mathematical model and algorithm process were given. Then evaluating the impacts of three kinds of charging strategies including disordered charging, time-of-use (TOU) charging price and smart charging on power grid through an example. The simulation results show that the smart charging strategy can effectively reduce the peak load and obtain better voltage distribution and lower power loss.In the case of regional power grid containing wind power and photovoltaic power generation, considering the vehicle-to-grid(V2G)model, a multi-objective coordinated dispatching model, in which the EVs, wind power and photovoltaic generation system were taken into account simultaneously, has been established, so that charging and discharging performance of EVs could be arranged reasonably. The model takes the minimum equivalent load fluctuation of regional power grid and the minimum charging price of EVs users as objective function, for the purpose of reducing the difference between the peak and the valley of load of power grid and promoting renewable energy absorption, also to improve the response positivity of EVs users. Based on the fuzzy processing of objective function, this problem was solved by using adaptive particle swarm optimization algorithm, and optimal dispatching scheme was obtained. Simulation results show the effectiveness of multi-objective model and feasibility of solving method.