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.


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    Title :

    Infrastructure planning for fast charging stations in a competitive market


    Contributors:
    Guo, Zhaomiao (author) / Deride, Julio (author) / Fan, Yueyue (author)


    Publication date :

    2016-04-06


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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