Optimization Design And Economical Operation Of Pure Electric Vehicles Swapping Station

Based on experiences of engaging in the electric bus swapping station process design and research on traction lithium-ion battery pack technique, utilizing long-term running data of Beijing Olympic Games Bus swapping station as well as Shanghai World Expo bus swapping station, the paper aims to reduce the construction cost, using cost of the swapping station, and to decreasethe charging load effects on distribution network. From the swapping station parameters design and its economic operation point of view, the research work can be summarized as follows:(1) By analyzing the bus operation features and the running data of the battery in the swapping stations, the distribution model of battery SOC of EV bus back to the swapping station, battery charging time model and charging power model are established; The design parameters calculation method for the charging station is proposed based on SOC distribution model of the power battery back to the station. The correction method to charging station parameters for various EV bus operation modes is investigated. In order to reduce the charging cost and construction cost of the charging station, the optimization of the departure time interval for the EV bus is developed.(2)The conditions test method for the lithium-ion battery including the power and the temperature effects is introduced to address the issues that charging time changes significantly caused by temperature and capacity recession and other factors.By proceeding comparative experiments, the main affect factors on the battery charging time is analyzed based on the equivalent circuit model. The mathematical model of the battery charging time is established considering the effects of battery temperature and capacity recession; and its engineering calculation threshold for lithium manganese oxide battery is determined. On the basis, considering the extension of the battery charging time, the redundancy design method of the swapping station core parameters is proposed.(3)The waiting time of the backup battery in the swapping station after full charged is first analyzed, baesd on the current industrial electricity Pricing Policy. The genetic algorithm (GA) is used to optimize the backup battery charging time for minimizing the difference between peak and valley power, reducing the cost of all day charging and realizing economic operation of the swapping station. According to actual running time of diverse periods of the bus and the average energy consumption in the different seasons, runing time correction coefficient of segments running through out the day and the energy consumption correction coefficient in the different seasons is introduced to accurately estimate the vehicles running time and the energy consumption at various seasons needed by GA optimization algorithm.The applicability of the proposed method is demonstrated based on the actual operating data of Beijing Olympic Games swapping station bus and typical operating conditions of the Beijing Public Transportation.The charging costs can be reduced by more than40%.(4)Based on analysis of load characteristics of the charging station as well as the main affecting factors, the back propagation (BP) neural network forecasting model and historical data extraction method based on fuzzy clustering are studied in this paper. The BP neural network load forecasting model is developed suitable for the EV bus swapping station.The statistical indicators of the historical data of fuzzy clustering, as well as search scope and quantity of the historical data needed by the BP neural network are determined, and short-term load forecasting method of the swapping station using BP neural network based on similar daily load samples is introduced, which is validated by the operation load data for one year of Beijing Olympic Games EV swapping station.lt is suggested that the estimation error is controlled within10%, which demonstrates the accuracy and effectiveness of the proposed method.The establishment of the short-term load forecasting method of the swapping station beneficial to electricity management and stable operation of the urban distribution network.