Optimal design of electric vehicle public charging system in an urban network for Greenhouse Gas Emission and cost minimization

Jinwoo Lee, Samer Madanat

    Research output: Contribution to journalArticle

    Abstract

    In this paper, we address the optimization problem of allocation of Electric Vehicle (EV) public fast charging stations over an urban grid network. The objective is to minimize Greenhouse Gas Emissions (GHG) under multiple constraints including a limited agency budget, accessibility of charging stations in every possible charging request and charging demands during peak hours. Additionally, we address bi-criteria problems to consider user costs as the second objective. A convex parsimonious model that depends on relatively few assumptions and input parameters is proposed and it is shown to be useful for obtaining conceptual insights for high-level planning. In a parametric study using a hypothetical urban network model generated based on realistic parameters, we show that GHG emissions decrease with agency budget, and that the reductions vary depending on multiple factors related to EV market and EV technologies. The optimal solutions found from the bi-criteria problems are shown to be close to the solution minimizing GHG emissions only, meaning that the emission minimizing policy can also minimize user costs.

    Original languageEnglish (US)
    Pages (from-to)494-508
    Number of pages15
    JournalTransportation Research Part C: Emerging Technologies
    Volume85
    DOIs
    StatePublished - Dec 1 2017

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    electric vehicle
    Electric vehicles
    Gas emissions
    Greenhouse gases
    costs
    Costs
    budget
    Planning
    Optimal design
    planning
    market

    Keywords

    • Convex system
    • Electric vehicle public fast charging stations allocation
    • Greenhouse Gas Emissions minimization
    • Optimization
    • Parsimonious model
    • Urban grid network

    ASJC Scopus subject areas

    • Civil and Structural Engineering
    • Automotive Engineering
    • Transportation
    • Computer Science Applications

    Cite this

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    title = "Optimal design of electric vehicle public charging system in an urban network for Greenhouse Gas Emission and cost minimization",
    abstract = "In this paper, we address the optimization problem of allocation of Electric Vehicle (EV) public fast charging stations over an urban grid network. The objective is to minimize Greenhouse Gas Emissions (GHG) under multiple constraints including a limited agency budget, accessibility of charging stations in every possible charging request and charging demands during peak hours. Additionally, we address bi-criteria problems to consider user costs as the second objective. A convex parsimonious model that depends on relatively few assumptions and input parameters is proposed and it is shown to be useful for obtaining conceptual insights for high-level planning. In a parametric study using a hypothetical urban network model generated based on realistic parameters, we show that GHG emissions decrease with agency budget, and that the reductions vary depending on multiple factors related to EV market and EV technologies. The optimal solutions found from the bi-criteria problems are shown to be close to the solution minimizing GHG emissions only, meaning that the emission minimizing policy can also minimize user costs.",
    keywords = "Convex system, Electric vehicle public fast charging stations allocation, Greenhouse Gas Emissions minimization, Optimization, Parsimonious model, Urban grid network",
    author = "Jinwoo Lee and Samer Madanat",
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    N2 - In this paper, we address the optimization problem of allocation of Electric Vehicle (EV) public fast charging stations over an urban grid network. The objective is to minimize Greenhouse Gas Emissions (GHG) under multiple constraints including a limited agency budget, accessibility of charging stations in every possible charging request and charging demands during peak hours. Additionally, we address bi-criteria problems to consider user costs as the second objective. A convex parsimonious model that depends on relatively few assumptions and input parameters is proposed and it is shown to be useful for obtaining conceptual insights for high-level planning. In a parametric study using a hypothetical urban network model generated based on realistic parameters, we show that GHG emissions decrease with agency budget, and that the reductions vary depending on multiple factors related to EV market and EV technologies. The optimal solutions found from the bi-criteria problems are shown to be close to the solution minimizing GHG emissions only, meaning that the emission minimizing policy can also minimize user costs.

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