Unit Commitment In Power Systems Considering Large-scale Electric Vehicles

The driving force of the modern development of electric vehicles is the development and utilization of new energy sources. With the introduction of demand side management and smart grid,as a controllable load with energy storage devices, large-scale EVs can be seen as distributed energy storages in the grid, also can effectively reduce unit operating costs and improve the acceptance of new energy power generation as well as the equipment utilization.Firstly, this paper analyzes the electric vehicle charging load influence factors, and the users travel rule is researched by probability and statistics, and then a method to forecast vehicle charging load based on Monte Carlo is proposed. Based on the EV day-ahead forecast data, this paper proposes a day-ahead schedulable capacity evaluation method of large-scale electric vehicle for V1 G control mode, considering the user demand and periods connected into gird. The forecasting method of vehicle charging load and day-ahead schedulable capacity is the base of grid operation control method within electric vehicles.Secondly, based on traditional unit commitment, this paper did some research on unit commitment in power systems considering large-scale electric vehicles. Compared to dispatch every single vehicle directly, the power gird interact with every single EV through the EV aggregator is more reasonable and feasible. Assuming that all electric vehicles integrated to the grid are managed by aggregators, this paper proposes that the charging load of each EV aggregator can be dispatched within the unit commitment model taking the controllability of the charging of EVs into consideration. This can be accomplished by assessing the upper and lower limit of charging load of each EV aggregator based on the grid connected EVs scenarios simulation using Monte Carlo method, and then UC models with or without wind power is proposed respectively. Cases study show that with the proposed UC model the wind abandon can be decreased as well as the cost of operation effectively.Finally, the scheduling priority comprehensive assessment system is established based on the evaluation index such as schedulable period proportion, possibility of unexpected incidents and battery consumption. Based on scheduling priority, EV charging plan hierarchical optimization model is proposed. Considering the user demand and other constraints, the upper objective is to minimize the sum of the square of difference between the actually and the required schedulable capacity of EV aggregator in every period while the lower objective is to minimize the sum of EV scheduling priority sequence in the whole scheduling period. Cases with 100 EVs shows that hierarchical optimization model can help EV aggregator to develop an appropriate electric vehicle charging plans.