Selection of charging sites for electric vehicles in the Republic of Korea based on fuzzy analytic hierarchy process

Lee, Byung-Hyun; Jung, Sin‐Ho; Sung, Jang-Hyun; Kim, Byung-Sik

doi:10.1007/s40042-021-00128-9

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…Efficient management of PEVCS distribution could support sustainability and resilience in dealing with environmental challenges by prioritizing the evaluation of flooding risks under the environment criteria. Hence, it is crucial to identify locations for the charging infrastructure that are not vulnerable to flood-related hazards, considering the country's susceptibility to periodic heavy rainfall and potential flooding [52].…”

Section: Resultsmentioning

confidence: 99%

Charging Ahead: Statistics on Electric Vehicle Charging Station Allocation and Uptake Trends in Malaysia

N. A. Syahirah,

R. N. Farah

2024

AMCI

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The emergence of electric vehicles is attributable to the accessibility of charging stations, which is essential in reducing EV drivers' range anxiety. EV batteries need to recharge after a certain number of miles driven. As a result, for EVs to be widely deployed, a sustainable charging station must be constructed. The National Electric Mobility Blueprint states that Malaysia's primary goal is for the nation to become the marketing hub for the EV industry by 2030. By 2030, Malaysia reportedly expects to have 125,000 electric vehicle charging stations. EVCS are available in many types, each with different charging capabilities and speeds. The most popular EVCS are slow charging stations, fast charging stations, battery swap charging stations, and wireless charging stations. The type of EVCS is discussed in this study, particularly from the perspectives of Malaysia. The mechanisms, advantages, disadvantages, and associated issues of these EVCS are thoroughly discussed. Furthermore, to reduce range anxiety among EV users and enhance EV adoptions in Malaysia, several criteria are considered in determining the suitable location for Photovoltaic Electric Vehicle Charging Stations. For future studies, all the selected criteria will be calculated using Multi-Criteria Decision-Making methods.

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Section: Resultsmentioning

confidence: 99%

Charging Ahead: Statistics on Electric Vehicle Charging Station Allocation and Uptake Trends in Malaysia

N. A. Syahirah,

R. N. Farah

2024

AMCI

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“…Karolemeas et al, [18] have demonstrated that proximity to transport hubs, density of marked and controlled parking spaces, and proximity to points of interest constitute the top three sub-criteria, while proximity to public services rank lower in significance among the sub-criteria. These findings underscore that an ideal charging station (CS) location should exhibit a high EV penetration rate, solid charging infrastructures secured in a given area, high road network density and high traffic volumes in city centers [19]. In determining a suitable site for EVCS, it is imperative to account for environmental considerations, with easiness of extension and re-establishment in the future emerging as the paramount criterion, followed by considerations such as greenhouse gas (GHG) reduction and fine particulate matter emission reduction, and destruction degree on urban vegetation and landscape [20].…”

Section: Literature Reviewmentioning

confidence: 95%

Towards Sustainable Mobility: Identifying Ideal Locations for Photovoltaic Electric Charging Stations (PEVCS) in Malaysia

Nur Amira Syahirah Azmar,

Raja Noor Farah Azura Raja Ma'amor Shah

2024

ARD

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Photovoltaic electric vehicle charging stations (PEVCS) has been highlighted as an inspiration for sustainable mobility due to its environmental friendliness, ability to reduce transportation issues and potential to improve air quality. The establishment of PEVCS networks along major routes is projected to significant increase EV adoption in Malaysia, reducing EV customers' range anxiety. Given the current deployment of several electric vehicle charging stations (EVCS) and a limited number of PEVCS in Malaysia, there is a compelling reason for increasing the quantity of PEVCS along routes to magnify its positive environmental impact. Adding to the previously described problems, this study seeks to identify suitable locations for PEVCS in Malaysia. The findings of the Need Analysis completed as part of this study were used to develop these site-selection criteria, which include both main and secondary factors. Finally, 41 sub-criteria were chosen for this study, which are divided into the following categories: society, economy, environment, technology, accessibility and proximity. In conclusion, these criteria provide a comprehensive framework for decision-makers and stakeholders to determine suitable spots for PEVCS in Malaysia, supporting sustainable mobility and improving the entire experience for electric vehicle users.

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“…Dynamic real-time data replaced static statistical data, and a simulation platform was established for location planning of EV charging stations in different cities and regions. Lee et al [16] comprehensively considered charging demand capability, user convenience, and installation convenience indices and developed a final charging-station location scheme using the charging infrastructure location index (CILI). Xiao et al [17] optimized the location of charging stations with the goal of minimizing the sum of the annual total cost of charging stations and the annual loss cost of EV users, divided the service scope of each charging station with the goal of minimizing user travel distance to the station, and combined the simulated annealing and Dijkstra algorithms to solve the planning model.…”

Section: Multi-objective Charging-station Location Optimizationmentioning

confidence: 99%

Optimization of Charging-Station Location and Capacity Determination Based on Optical Storage, Charging Integration, and Multi-Strategy Fusion

Wang,

Wu,

Sun

2024

JGELCD

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To reduce electric vehicle carbon dioxide emissions while charging and increase charging pile utilization, this study proposes an optimization method for charging-station location and capacity determination based on multi-strategy fusion that considers the optical-storage charging station. By analyzing the characteristics of vehicle trajectory data, the dwell points that support charging are extracted; the center point of the dwell area is obtained through k-means clustering, indicating the candidate site of a charging station and optical-storage charging station. The process for determining demand points and quantities is described as follows. Set the parking lot as the demand point; select the period with the most vehicle stops, and determine the demand according to the proximity principle. Using the investment cost, user time cost, and total carbon dioxide emissions from charging as the targets, a data-driven co-evolutionary model is established. It is solved using the multi-objective particle swarm optimization algorithm. Further, the analytic hierarchy process is used to determine the optimal location and sizing scheme. Empirical analysis is completed using Beijing taxi track data as an example. The experiments show that after constructing an optical-storage charging station, the number of charging piles can be reduced by improving the charging pile utilization rate, and the investment cost can be effectively controlled. The station is built at a location with a large demand, effectively reducing the carbon dioxide emissions caused by charging and indirectly reducing user time cost.

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Selection of charging sites for electric vehicles in the Republic of Korea based on fuzzy analytic hierarchy process

Cited by 5 publications

References 14 publications

Charging Ahead: Statistics on Electric Vehicle Charging Station Allocation and Uptake Trends in Malaysia

Charging Ahead: Statistics on Electric Vehicle Charging Station Allocation and Uptake Trends in Malaysia

Towards Sustainable Mobility: Identifying Ideal Locations for Photovoltaic Electric Charging Stations (PEVCS) in Malaysia

Optimization of Charging-Station Location and Capacity Determination Based on Optical Storage, Charging Integration, and Multi-Strategy Fusion

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