Publication Detail

Infrastructure Planning for Fast Charging Stations in a Competitive Market

UCD-ITS-RP-16-38

Reprint

Sustainable Transportation Energy Pathways (STEPS), National Center for Sustainable Transportation

Suggested Citation:
Guo, Zhaomiao, Julio Deride, Yueyue Fan (2016) Infrastructure Planning for Fast Charging Stations in a Competitive Market. Transportation Research Part C 68 (July 2016), 216 - 227

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.

Keywords: EV charging infrastructure, Multi-agent optimization, Nash equilibrium, Lopsided convergence