Charging station planning based on the accumulation prospect theory and dynamic user equilibrium

Abstract Large-scale use of electric vehicles will greatly increase the traffic pressure on urban road network. Therefore, planning of charging stations for electric vehicles considering charging demand and transportation network is particularly important for the coordinated development of electric...

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Main Authors: Qiu Heting, Dou Shuihai, Shang Huayan, Zhang Jun
Format: Article
Language:English
Published: Springer 2021-06-01
Series:Complex & Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1007/s40747-021-00414-w
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author Qiu Heting
Dou Shuihai
Shang Huayan
Zhang Jun
author_facet Qiu Heting
Dou Shuihai
Shang Huayan
Zhang Jun
author_sort Qiu Heting
collection DOAJ
description Abstract Large-scale use of electric vehicles will greatly increase the traffic pressure on urban road network. Therefore, planning of charging stations for electric vehicles considering charging demand and transportation network is particularly important for the coordinated development of electric vehicles and intelligent transportation. Under the condition of bounded rationality, this paper considers such factors as the travel utility perception difference between the users of fuel vehicles and electric vehicles, the time-varying of traffic flow, the location and service level of charging stations. On this basis, combining the cumulative prospect theory, dynamic traffic flow allocation and charging demands, a two-level programming model is established to solve the problem of charging station site selection. The upper layer is a system optimal model, the goal is to minimize the travel time of the network. The lower model describes the time-variability of departure time and the randomness of charging and travel behaviors, establishes the dynamic user equilibrium model and designs the heuristic algorithm. The validity of the model and algorithm is verified by a numerical example. Through the simulation experiment, the optimal location scheme of charging station under different electric vehicle proportion is obtained, and the driving characteristics of two types of vehicles are analyzed. Compared with the traditional model, it is found that the charging station planning considering bounded rationality can achieve higher road network traffic efficiency with fewer charging piles.
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spelling doaj.art-503b9b56b11e44f98be2e55f246d7f412023-06-11T11:29:07ZengSpringerComplex & Intelligent Systems2199-45362198-60532021-06-01932521253910.1007/s40747-021-00414-wCharging station planning based on the accumulation prospect theory and dynamic user equilibriumQiu Heting0Dou Shuihai1Shang Huayan2Zhang Jun3School of Management and Engineering, Capital University of Economics and BusinessSchool of Mechanical and Electrical Engineering, Beijing Institute of Graphic CommunicationSchool of Management and Engineering, Capital University of Economics and BusinessSchool of Management and Engineering, Capital University of Economics and BusinessAbstract Large-scale use of electric vehicles will greatly increase the traffic pressure on urban road network. Therefore, planning of charging stations for electric vehicles considering charging demand and transportation network is particularly important for the coordinated development of electric vehicles and intelligent transportation. Under the condition of bounded rationality, this paper considers such factors as the travel utility perception difference between the users of fuel vehicles and electric vehicles, the time-varying of traffic flow, the location and service level of charging stations. On this basis, combining the cumulative prospect theory, dynamic traffic flow allocation and charging demands, a two-level programming model is established to solve the problem of charging station site selection. The upper layer is a system optimal model, the goal is to minimize the travel time of the network. The lower model describes the time-variability of departure time and the randomness of charging and travel behaviors, establishes the dynamic user equilibrium model and designs the heuristic algorithm. The validity of the model and algorithm is verified by a numerical example. Through the simulation experiment, the optimal location scheme of charging station under different electric vehicle proportion is obtained, and the driving characteristics of two types of vehicles are analyzed. Compared with the traditional model, it is found that the charging station planning considering bounded rationality can achieve higher road network traffic efficiency with fewer charging piles.https://doi.org/10.1007/s40747-021-00414-wCharging station planningAccumulation prospect theoryDynamic user equilibriumMixed traffic flowComplex system
spellingShingle Qiu Heting
Dou Shuihai
Shang Huayan
Zhang Jun
Charging station planning based on the accumulation prospect theory and dynamic user equilibrium
Complex & Intelligent Systems
Charging station planning
Accumulation prospect theory
Dynamic user equilibrium
Mixed traffic flow
Complex system
title Charging station planning based on the accumulation prospect theory and dynamic user equilibrium
title_full Charging station planning based on the accumulation prospect theory and dynamic user equilibrium
title_fullStr Charging station planning based on the accumulation prospect theory and dynamic user equilibrium
title_full_unstemmed Charging station planning based on the accumulation prospect theory and dynamic user equilibrium
title_short Charging station planning based on the accumulation prospect theory and dynamic user equilibrium
title_sort charging station planning based on the accumulation prospect theory and dynamic user equilibrium
topic Charging station planning
Accumulation prospect theory
Dynamic user equilibrium
Mixed traffic flow
Complex system
url https://doi.org/10.1007/s40747-021-00414-w
work_keys_str_mv AT qiuheting chargingstationplanningbasedontheaccumulationprospecttheoryanddynamicuserequilibrium
AT doushuihai chargingstationplanningbasedontheaccumulationprospecttheoryanddynamicuserequilibrium
AT shanghuayan chargingstationplanningbasedontheaccumulationprospecttheoryanddynamicuserequilibrium
AT zhangjun chargingstationplanningbasedontheaccumulationprospecttheoryanddynamicuserequilibrium