Highlights We study business-driven charging infrastructure planning in competitive market. A network-based multi-agent optimization model is developed. Solution method based on variational convergence theorems is designed.
Abstract Most existing studies on EV charging infrastructure planning take a central planner’s perspective, by assuming that investment decision on charging facilities can be controlled by a single decision entity. In this paper, we establish modeling and computational methods to support business-driven EV charging infrastructure investment planning problem, where the infrastructure system is shaped by collective actions of multiple decision entities who do not necessarily coordinate with each other. A network-based multi-agent optimization modeling framework is developed to simultaneously capture the selfish behaviors of individual investors and travelers and their interactions over a network structure. To overcome computational difficulty imposed by non-convexity of the problem, we rely on recent theoretical development on variational convergence of bivariate functions to design a solution algorithm with analysis on its convergence properties. Numerical experiments are implemented to study the performance of proposed method and draw practical insights.
Infrastructure planning for fast charging stations in a competitive market
Tramsportation Research, Part C: Emerging Technologies ; 68 ; 215-227
2016-04-06
13 pages
Article (Journal)
Electronic Resource
English
Infrastructure planning for fast charging stations in a competitive market
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