Study On Electric Taxi Charging Station Planning Based On Destination Choice

The development of electric vehicle(EV) is generally confirmed as an important way to ensure energy security and low carbon economy by all countries in the world. In recent years, with EV technology advancing and government supporting the popularization of charging piles in public and residential areas, large EV charing stations will mainly serve electric taxis(ETs). As ETs gradually replace traditional fuel taxis, existing charging stations will be unable to meet the increasing charging demand. Therefore, study on how to add ET charging stations into the existing charging network has theoretical and pratical significance.This paper mainly focus on the following aspects:(1) Determine the capacity of each station by constructing ET operating model. Firstly, the target area is divided into several regions. On the basis of collecting trip distribution data, single-restraint gravity model and Logit model are applied for acquiring with-passenger and empty-run destination choice probability respectively. Secondly, according to the balance between generation and attraction, ET load factor of each region is obtained by empty-run ET distribution. Finally, considering the ET owership, forecast the charging load and determine the capacity of each charging station by building ET operating model which simulates the action of empty-run and with-passenger ET.(2) To improve the ET operating model. In order to solve the problem of extensive destination options and overly complex computation, the ET operating model is improved by selecting destination hierarchically and the ET operating behavior is also refined. The case simulation result shows that The improved model is not only suitable for larger dimensionality but also has faster running speed.(3) Based on the multi-objective evolutionary algorithm, an ET charging station planning model is built to research how to add new stations into the existing charging network. Considering the existing charging network, the charging load and capacity of each station in the planning scheme are obtained by ET operating model. Taking total cost, convenience of charging and equipment utilization rate as indexs, construct an ET charging station planning model based on the multi-objective evolutionary algorithm. NSGA-Ⅱ and SPEA-Ⅱ algorithms are applied to solve the problems, such as the amount, location and capacity of new-built ET charging stations. The effectiveness of the model is verified by the case study and compared with NSGA-Ⅱ algorithm, SPEA-Ⅱ algorithm is more efficient for the model.