Framework for planning of EV charging infrastructure: Where should cities start?

Torkey, Alaa; Abdelgawad, Hossam

doi:10.1016/j.tranpol.2022.09.015

“…This approach is generally characterized by the leverage of innovative ICT solutions to improve the quality of life for inhabitants by enhancing the quality and efficiency of urban services, positioning cities as sources of economic growth, and as a major contributor to the national economy. Formerly, most countries and cities, including Egypt, and their governments considered sustainability as an afterthought in city development goals (Badran, 2023 ;Embarak, 2022;Torkey & Abdelgawad, 2022).…”

Section: Government Policies and Regulationsmentioning

confidence: 99%

The Role of Public-Private Partnerships in Sustainable Smart City Management in Egypt.

Samir Abdelaziz

2024

المجلة العلمية للدراسات التجارية والبيئية

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“…Using this method [5], congestion can be assessed, and the optimal node placement can be determined. The global adoption of electric vehicles (EVs) in recent years has spurred research on the ideal placement of EV charging stations [22][23][24][25], with the queueing theory playing an increasingly pivotal role [26][27][28][29][30][31]. In such studies, EV charging stations are often modeled as multi-server queues, such as M/M/s, rather than as queueing networks.…”

Section: Related Workmentioning

confidence: 99%

Proposal for Optimizing Number of Servers in Closed BCMP Queueing Network

Mizuno,

Komiyama,

Ohba

2023

Preprint

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In this study, we use a closed BCMP queueing network model designed for multiple customer classes and servers to optimize the number of servers at each node. This optimization is achieved by setting an upper limit on the number of servers and using an objective function that combines the standard deviation of the average number of customers in the system with the server installation cost. We use a genetic algorithm with parallel computations for the optimization process. Our findings demonstrate that this approach is viable for closed BCMP network models that require extensive computational resources. The optimal server count is validated by comparing the optimization results with the maximum number of servers utilized. Node popularity is predetermined, and a gravity model is employed to generate transition probabilities, rendering the model applicable to real-world scenarios. Our optimization results indicate that both the node popularity and distance between nodes influence the server count. Furthermore, simulations were conducted to evaluate the effect of the number of servers on the optimization outcomes. Allowing variations in the node count, location, and popularity makes this study flexible and adaptable to various real-world scenarios, such as transportation systems, healthcare facilities, and commercial spaces. Moreover, by providing an efficient and scalable solution, this study serves as a cornerstone for future research in this field and offers a practical tool for facility managers aiming to minimize both congestion and operational costs.

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Proposal for optimizing number of servers in closed BCMP queueing network

Mizuno,

Komiyama,

Ohba

2024

Int J Data Sci Anal

0

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In this study, we use a closed BCMP queueing network model designed for multiple customer classes and servers to optimize the number of servers at each node. This optimization is achieved by setting an upper limit on the number of servers and using an objective function that combines the standard deviation of the average number of customers in the system with the server installation cost. We use a genetic algorithm with parallel computations for the optimization process. Our findings demonstrate that this approach is viable for closed BCMP network models that require extensive computational resources. The optimal server count is validated by comparing the optimization results with the maximum number of servers utilized. Node popularity is predetermined, and a gravity model is employed to generate transition probabilities, rendering the model applicable to real-world scenarios. Our optimization results indicate that both the node popularity and distance between nodes influence the server count. Furthermore, simulations were conducted to evaluate the effect of the number of servers on the optimization outcomes. Allowing variations in the node count, location, and popularity makes this study flexible and adaptable to various real-world scenarios, such as transportation systems, healthcare facilities, and commercial spaces. Moreover, by providing an efficient and scalable solution, this study serves as a cornerstone for future research in this field and offers a practical tool for facility managers aiming to minimize both congestion and operational costs.

show abstract

Framework for planning of EV charging infrastructure: Where should cities start?

Cited by 9 publications

References 16 publications

The Role of Public-Private Partnerships in Sustainable Smart City Management in Egypt.

The Role of Public-Private Partnerships in Sustainable Smart City Management in Egypt.

Proposal for Optimizing Number of Servers in Closed BCMP Queueing Network

Proposal for optimizing number of servers in closed BCMP queueing network

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