Optimal Control Strategy Of Electric Vehicle Battery Swapping Station

In order to deal with energy and environmental crisis, the electric vehicle industry rapidly developed in our country. Swapping stations, built as supporting facilities, are becoming a new load type with the characteristic of flexible power demand. Due to the battery in the electric vehicle, swapping station can be treated as generator or load. By fully tapping storage capability of electric vehicle swapping station, reasonable decision can be made to reduce the influence of unordered swapping on the power system. What’s more, swapping station can provide reserve in case of emergency. Therefore, study of the optimal control strategy for electric vehicle swapping station has important significances.In order to realize the goal of electric vehicle swapping station optimal control, swapping demand forecasting and optimizing control decision based on the forecast result are necessary. Swapping demand forecasting can be achieved by study of electric vehicle trip rule and limited value of swapping point. It also can be achieved by extracting rules or models from huge swapping history data of stations. To obtain optimal swapping strategy, optimization model are usually built with the objectives of operating cost or security of power system, considering battery capacity constraints, swapping power constraints of swapping points and other constraints.Currently, there are several following issues of swapping demand forecasting and control strategy optimization:① currently, most swapping demand forecasting are obtained by deterministic forecasting algorithm. The results can’t reflect the uncertainty of swapping demand. ② most optimization model takes swapping power as control variables. However, limited by the number of batteries, the results cannot coordinate with real operation. ③ research about coordinate operation decision about renewable generation and electric vehicle swapping station by exchanging batteries is less.Under the above background, firstly, using Markov forecast method, a swapping demand forecast model is proposed in basis on discretizing swapping demand continuous state space. The states probability of electric vehicle stations gotten by the forecasting model can provide fully decision basises. Secondly, based on time of use electricity price, a two level optimization model about electric vehicle swapping station control is proposed, with number of swapping batteries as the decision variable. The first level of the model is optimizing the operating cost, and the second level is maximizing the number of full batteries without increasing the operating cost. During the optimization, uncertainty of the swapping demand is considered. Lastly, based on analyzing the will of switching batteries of swapping stations, a battery switching model between swapping stations and ESS of renewable power station is proposed to maximizing the consolidated income. The models proposed in this paper have been tested on real systems, and the effectiveness has been demonstrated by the test results.