详情

原文传递 OPTIMAL FLEET DEPLOYMENT MODEL FOR ELECTRIC VEHICLE SHARING SYSTEMS

题名：	OPTIMAL FLEET DEPLOYMENT MODEL FOR ELECTRIC VEHICLE SHARING SYSTEMS
正文语种：	中文
作者：	盧宗成
关键词：	Public electric vehicles;Shared mobility systems;Time-space networks;Fleet deployment
摘要：	This study develops a mathematical programming model to determine optimal deployment of a given fleet of plug-in electric vehicles (EVs) to the stations of a leisure-oriented EV-sharing system. The objective is to maximize the profit of the system operator. The proposed model is developed based on an EV-flow time-space network that describes the movements of EVs in the spatial and temporal dimensions. In addition, the model takes into account the operational characters of plug-in EVs, including energy consumption, battery capacity and charging requirement. To examine the performance of the proposed model, this study conducts a set of computational experiments on two problem instances (or scenarios) of different sizes (in terms of numbers of stations and EVs) generated based on the EV-Sharing system deployed in Sun Moon Lake national park in Nantou, Taiwan. The base case scenario (scenario 1) is designed according to the current status of the system, including 2 stations and 19 EVs. Considering that the system will be expanded in the near future, the other scenario with more stations and EVs is also generated; scenario 2 has 3 stations and 30 EVs. These two problem instances of the model are solved using CPLEX. The results show that the proposed model is effective in obtaining optimal fleet allocations for the EV-Sharing system. We also conduct a sensitivity analysis to examine the impact of different demand levels of on the fleet allocation results of the model. The results of the sensitivity analysis are discussed and suggestions for dealing with unmet demand, such as real-time dispatching or reallocation of EVs and increasing the fleet size, are presented. The fleet allocation results obtained by solving the model can be used as a reference for the system operator to improve the overall operational efficiency and service level of the system.
期刊名称：	运输计划
出版年：	2017
期：	02
页码：	191-216