A Study On Charging-Discharging Behaviors Of Large-scale Electric Vehicles And Their Impact On Power Grid

The large scale application of EVs (electric vehicles) is an inevitable trend at home andabroad. When lots of EVs are plugged into the grid, the impact of their charging load on thegrid is not negligible; while the development of V2G technology allows EVs to discharge tothe grid, it provides an opportunity for improving the safety and economic operation of thegrid. Thus an issue appears: in order to exert a favorable influence on the grid, how to guideor control large amounts of EVs’ charging/discharging behaviors. EVs’ charging/dischargingbehaviors are influenced by two factors: price mechanism which is an indirect factor andaggregators’ are direct dispatching according to the power system. This thesis studies EVs’charging behaviors under different price mechanisms and EVs’ charging and dischargingbehaviors based on the UC (Unit Commitment), and then observes the impact of thesecharging/discharging loads on the grid.When studying the impact of EVs’ charging on the grid under different pricemechanisms, this thesis firstly builds specific models of EVs’ behaviors, considering variousfactors such as travel distance, charging mode, and charging time. Based on the models, fourcharging scenarios are set, considering comprehensively the factors of charging mode, pricemechanism and operating agencies. Afterwards the Monte Carlo method is used to evaluatethe impact of scales of EVs on the daily load curve in Guangzhou. The results show thatEVs’ charging behaviors under different price mechanisms have different influence on theload curve: in some cases, EVs’ charging loads can increase the valley loads, in others theywill add other loads to the peak loads.When V2G is considered, this thesis studies scheduled EVs’ charging/dischargingbehaviors from the perspective of UC problems. In the presented UC model, the targetfunction is the minimum of the weighted sum of running cost of all units a nd EVs’discharging cost, and the optimization variables are the numbers of EVs’ charging anddischarging and all units’ status and output powers; moreover, the constraints of the powersystem like power balance constraint and EV users’ situations like desired departure state ofcharge level (SOC) are considered. Compared with the UC models incorporating EVs before,not only does the model this thesis presents take into consideration both the constraints of the power system and specific needs of EV users, but it can also observe all EVs’ SOC anytime. Based on the linear model, MIP solver of GAMS is used to solve the UC problems. A10-unit24-hour UC problem is employed to demonstrate the feasibility and efficiency of thedeveloped model.