Coordinated routing optimization and charging scheduling in a multiple-charging station system: A strategic bilevel multi-objective programming

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00381219" target="_blank" >RIV/68407700:21230/25:00381219 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.segan.2025.101659" target="_blank" >https://doi.org/10.1016/j.segan.2025.101659</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.segan.2025.101659" target="_blank" >10.1016/j.segan.2025.101659</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Coordinated routing optimization and charging scheduling in a multiple-charging station system: A strategic bilevel multi-objective programming

Popis výsledku v původním jazyce

Effectively managing EV charging queues not only alleviates traffic congestion in high-demand areas but also improves user satisfaction by minimizing waiting times. This framework enhances overall system efficiency by better distributing the concentration of EVs during peak periods. This research investigates collaborative mechanisms from the perspectives of various stakeholders, including charging stations (CSs) and EVs, to optimize the charging process. A route optimization model is employed to direct EVs toward the most suitable CSs, followed by the introduction of two scheduling models: (1) a social welfare maximization model and (2) a game-theoretic iterative framework. These models aim to optimize EV charging locations while increasing CS profitability. EVs scheduling is performed using a mixed-integer non-linear programming (MINLP) approach, offering critical insights into its applicability across different scenarios. The numerical results demonstrate that coordinated EV scheduling substantially enhanc

Název v anglickém jazyce

Coordinated routing optimization and charging scheduling in a multiple-charging station system: A strategic bilevel multi-objective programming

Popis výsledku anglicky

Effectively managing EV charging queues not only alleviates traffic congestion in high-demand areas but also improves user satisfaction by minimizing waiting times. This framework enhances overall system efficiency by better distributing the concentration of EVs during peak periods. This research investigates collaborative mechanisms from the perspectives of various stakeholders, including charging stations (CSs) and EVs, to optimize the charging process. A route optimization model is employed to direct EVs toward the most suitable CSs, followed by the introduction of two scheduling models: (1) a social welfare maximization model and (2) a game-theoretic iterative framework. These models aim to optimize EV charging locations while increasing CS profitability. EVs scheduling is performed using a mixed-integer non-linear programming (MINLP) approach, offering critical insights into its applicability across different scenarios. The numerical results demonstrate that coordinated EV scheduling substantially enhanc

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Sustainable Energy, Grids and Networks

ISSN

2352-4677

e-ISSN

2352-4677

Svazek periodika

42

Číslo periodika v rámci svazku

101659

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

1-17

Kód UT WoS článku

001431513500001

EID výsledku v databázi Scopus

2-s2.0-85218266527