Optimization of incentive polices for plug-in electric vehicles |
| |
| Institution: | 1. Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL 60208, USA;2. Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48825, USA;3. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China;4. School of Business Administration, Southwestern University of Finance and Economics, Chengdu, PR China;1. Department of Civil and Environmental Engineering, University of South Florida, FL 33620, United States;2. Transportation Solutions and Technology Applications Division, Leidos, Inc., VA 22101, United States;3. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;1. Department of Industrial and Systems Engineering, University at Buffalo, SUNY, USA;2. Department of Industrial and Management Systems Engineering, University of South Florida, USA;1. School of Business Administration, Southwestern University of Finance and Economics, PR China;2. School of Automotive and Transportation Engineering, Hefei University of Technology, PR China;3. California PATH, University of California, Berkeley, Richmond, CA, United States;4. Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, United States;1. Technical University of Denmark (DTU), Department of Transport, Lyngby, Denmark;2. Technische Universität Dresden, Institute of Transport & Economics, Faculty of Traffic Sciences, 01062 Dresden, Germany;3. Technische Universität Dresden, Faculty of Traffic Sciences, 01062 Dresden, Germany;4. The University of Queensland, School of Civil Engineering, Queensland, Australia |
| |
| Abstract: | High purchase prices and the lack of supporting infrastructure are major hurdles to the adoption of plug-in electric vehicles (PEVs). It is widely recognized that the government could help break these barriers through incentive policies, such as offering rebates to PEV buyers or funding charging stations. The objective of this paper is to propose a modeling framework that can optimize the design of such incentive policies. The proposed model characterizes the impact of the incentives on the dynamic evolution of PEV market penetration over a discrete set of time intervals, by integrating a simplified consumer vehicle choice model and a macroscopic travel and charging model. The optimization problem is formulated as a nonlinear and non-convex mathematical program and solved by a specialized steepest descent direction algorithm. We show that, under mild regularity conditions, the KKT conditions of the proposed model are necessary for local optimum. Results of numerical experiments indicate that the proposed algorithm is able to obtain satisfactory local optimal policies quickly. These optimal policies consistently outperform the alternative policies that mimic the state-of-the-practice by a large margin, in terms of both the total savings in social costs and the market share of PEVs. Importantly, the optimal policy always sets the investment priority on building charging stations. In contrast, providing purchase rebates, which is widely used in current practice, is found to be less effective. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
