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Relevant bibliographies by topics / Charging station location selection

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Academic literature on the topic 'Charging station location selection'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Charging station location selection"

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Qin, Jianxin, Jing Qiu, Yating Chen, Tao Wu, and Longgang Xiang. "Charging Stations Selection Using a Graph Convolutional Network from Geographic Grid." Sustainability 14, no. 24 (2022): 16797. http://dx.doi.org/10.3390/su142416797.

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Electric vehicles (EVs) have attracted considerable attention because of their clean and high-energy efficiency. Reasonably planning a charging station network has become a vital issue for the popularization of EVs. Current research on optimizing charging station networks focuses on the role of stations in a local scope. However, spatial features between charging stations are not considered. This paper proposes a charging station selection method based on the graph convolutional network (GCN) and establishes a charging station selection method considering traffic information and investment cos

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Keawthong, Pichamon, Veera Muangsin, and Chupun Gowanit. "Location Selection of Charging Stations for Electric Taxis: A Bangkok Case." Sustainability 14, no. 17 (2022): 11033. http://dx.doi.org/10.3390/su141711033.

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The transition from ICE to BEV taxis is one of the most important methods for reducing fossil fuel consumption and air pollution in cities such as Bangkok. To support this transition, an adequate number of charging stations to cover each area of charging demand must be established. This paper presents a data-driven process for determining suitable charging locations for BEV taxis based on their characteristic driving patterns. The location selection process employs GPS trajectory data collected from taxis and the locations of candidate sites. Suitable locations are determined based on estimate

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Ma, Hao, Wenhui Pei, Qi Zhang, Di Xu, and Yongjing Li. "Location of Electric Vehicle Charging Stations Based on Game Theory." World Electric Vehicle Journal 14, no. 5 (2023): 128. http://dx.doi.org/10.3390/wevj14050128.

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In order to solve the design problem of electric vehicle charging station distribution, based on the consideration of user and investor costs, this paper establishes a mixed integer model for charging station site selection based on game theory ideas. Among them, the user cost is determined by two indicators, namely, the cost of time for users to reach the charging station and the cost of time for users to wait in line, while the cost of the charging station is determined by the construction cost and the daily operation and maintenance cost. In the established model, the hierarchical analysis

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Zhang, Shiye. "Location Selection of Electric Vehicles Charging Stations Based on Analytical Hierarchy Process and Clustering Algorithm." Advances in Engineering Technology Research 6, no. 1 (2023): 631. http://dx.doi.org/10.56028/aetr.6.1.631.2023.

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In recent years, the charging infrastructure for electric vehicles (EVs) in China has been developing quickly, yet the charging station industry still faces problems such as unreasonable layout, difficulty in profitability and limited coverage. Based on this, this paper systematically compared the key factors of charging facility location and used the AHP method to measure the degree of influence of various factors at different levels on the location of charging stations of enterprises, so as to establish a scientific and reasonable evaluation model for the location of charging stations. Secon

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Hehuan and GeQin. "Location planning of electric taxi charging station based on driving trajectory." E3S Web of Conferences 271 (2021): 01024. http://dx.doi.org/10.1051/e3sconf/202127101024.

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With the vigorous development of energy technology, the promotion and use of electric vehicles has brought new vitality to the development of ecological environment. According to the big data of taxi travel trajectory, we can get the idle rule of taxi operation time. Taking the idle time and location of taxi as the demand hot spot, taking the location points along the road network of the research area as the candidate points, this paper uses ArcGIS to do the location planning of charging station, so that the charging station can reduce the charging anxiety of taxi drivers, meet the charging de

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Yi, Tao, Xiao-bin Cheng, Hao Zheng, and Jin-peng Liu. "Research on Location and Capacity Optimization Method for Electric Vehicle Charging Stations Considering User’s Comprehensive Satisfaction." Energies 12, no. 10 (2019): 1915. http://dx.doi.org/10.3390/en12101915.

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The development of electric vehicles has significant value for the sustainable utilization of energy resources. However, the unreasonable construction of charging stations causes problems such as low user satisfaction, waste of land resources, unstable power systems, and so on. Reasonable planning of the location and capacity of charging stations is of great significance to users, investors and power grids. This paper synthetically considers three indicators of user satisfaction: charging convenience, charging cost and charging time. Considering the load and charging requirements, the model of

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Shi, Tengyuan, and Jin Shen. "Locating and Sizing Planning of Electric Vehicle Battery-swapping Stations Considering User Path Selection." Journal of Physics: Conference Series 2479, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1742-6596/2479/1/012001.

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Abstract According to the characteristics of an electric vehicle’s charging mode and considering the user path selection, a two-level programming optimization model of EV battery-swapping station locating, and sizing planning is established. The daily power exchange demand load is predicted, and the service area of the battery-swapping station is divided by the Voronoi diagram. The upper model optimizes the location, and the optimized number of battery-swapping stations is passed to the lower model to realize the constant volume optimization. Finally, the feasibility and rationality of the opt

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Zhang, Hong, and Feifan Shi. "A multi-objective site selection of electric vehicle charging station based on NSGA-II." International Journal of Industrial Engineering Computations 15, no. 1 (2024): 293–306. http://dx.doi.org/10.5267/j.ijiec.2023.9.009.

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The planning of charging infrastructure is crucial to developing electric vehicles. Planning for charging stations requires considering several variables, including building costs, charging demand, and coverage levels. It might be advantageous to use a multi-objective optimization method based on the NSGA-II. We need to address the current problems in choosing the location of electric vehicle charging stations. Firstly, urban land use is divided into five functional areas, and the TF-IDF algorithm is applied to the division of functional areas. A combined clustering algorithm is proposed to cl

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Zhu, Guangyuan, Weiqing Wang, and Wei Zhu. "Research on the Location and Capacity Determination Strategy of Off-Grid Wind–Solar Storage Charging Stations Based on Path Demand." Processes 13, no. 3 (2025): 786. https://doi.org/10.3390/pr13030786.

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To address the challenges of cross-city travel for different types of electric vehicles (EV) and to tackle the issue of rapid charging in regions with weak power grids, this paper presents a strategic approach for locating and sizing highway charging stations tailored to such grid limitations. Initially, considering the initial EV state of charge, a path-demand-based model for EV charging station location–allocation is proposed to optimize station numbers and enhance vehicle flow, which indicates the passing rate of vehicles. Subsequently, a capacity configuration model is formulated, integrat

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Gkiotsalitis, Konstantinos, Dimitrios Rizopoulos, Marilena Merakou, Christina Iliopoulou, Tao Liu, and Oded Cats. "Electric bus charging station location selection problem with slow and fast charging." Applied Energy 382 (March 2025): 125242. https://doi.org/10.1016/j.apenergy.2024.125242.

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Dissertations / Theses on the topic "Charging station location selection"

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Du, Yunke. "PEV Charging Demand Estimation and Selection of Level 3 Charging Station." University of Akron / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=akron1367243693.

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Jochem, Patrick, Eckhard Szimba, and Melanie Reuter-Oppermann. "How many fast-charging stations do we need along European highways?" Elsevier, 2019. https://publish.fid-move.qucosa.de/id/qucosa%3A72227.

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For a successful market take-up of plug-in electric vehicles, fast-charging stations along the highway network play a significant role. This paper provides results from a first study on estimating the minimum number of fast-charging stations along the European highway network of selected countries (i.e., France, Germany, the Benelux countries, Switzerland, Austria, Denmark, the Czech Republic, and Poland) and gives an estimate on their future profitability. The combination of a comprehensive dataset of passenger car trips in Europe and an efficient arc-cover-path-cover flow-refueling location

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Wu, Fei. "Electric Vehicle Charging Network Design and Control Strategies." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1479900508609434.

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Fekete, P. L. "An approach to potential evaluation of a contactless energy supply infrastructure for occasional recharging in production related, non-automated material handling." Thesis, Coventry University, 2017. http://curve.coventry.ac.uk/open/items/ea965735-b09d-4ebb-9fc8-e2533bece313/1.

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Significant advances have been made in the research and development of electric vehicles (EV’s). Along with the major challenge of energy storage, being also addressed is the efficient design of system energy transfer and consumption. This has had the effect of fundamentally changing perspectives across the mobility and transportation sector. Applied predominantly to road-going vehicles, the industrial context of non-road Electric Vehicles (nrEV’s) and specifically the use of manned electric forklift trucks integrated within the production related materials handling system has, to-date, receiv

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Ghias, Nezhad Omran Nima. "Power grid planning for vehicular demand: forecasting and decentralized control." IEEE Transactions on Smart Grid, 2014. http://hdl.handle.net/1993/23891.

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Temporal and spatial distribution of incoming vehicular charging demand is a significant challenge for the future planning of power systems. In this thesis the vehicular loading is-sue is categorized into two classes of stationary and mobile; they are then addressed in two phases. The mobile vehicular load is investigated first; a location-based forecasting algorithm for the charging demand of plug-in electric vehicles at potential off-home charging stations is proposed and implemented for real-world case-studies. The result of this part of the re-search is essential to realize the scale of f

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LIN, PEI-YU, and 林佩瑜. "Location Selection Problem for Electric Bus Charging Station Considering the Different Charging Types." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/5ec7rj.

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碩士<br>國立雲林科技大學<br>工業工程與管理系<br>107<br>In recent years, the global warming problem has been serious. Countries have begun to address the issue of energy consumption and are committed to developing energy-saving and carbon-reduction technologies. The Chinese government actively promotes Green Transport and adopted the “Air Pollution Prevention Strategy” in 2017 to include electric buses as key subsidies and encourage the replacement of large diesel vehicles. In response to the policy, the CPC Corporation indicated that the gas station will be transformed into a "Smart Green Energy Gas Station" in

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KE, YEN-KAI, and 柯諺凱. "Decision Analysis of Location Selection Model of Electric Vehicle Charging Stations." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8jc397.

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碩士<br>輔仁大學<br>資訊管理學系碩士在職專班<br>106<br>An electric vehicle charging station, also called EV charging station, is an element in an infrastructure that supplies electric energy for the recharging of electric vehicles, such as plug-in electric vehicles, including electric cars, neighborhood electric vehicles and plug-in hybrids. Since many transnational famous automobile factories have invested in electric vehicles and charging equipment of innovation research and applications for a long time, recently, such efforts and important breakthroughs incur a lot of vigorous development in the Industry of

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Huang, Po-Wei, and 黃柏瑋. "Optimization model for city bus depot and charging station location problems." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/h2g78p.

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碩士<br>國立中央大學<br>土木工程學系<br>107<br>With the rapid increase of urban population, the fuel consumption of urban buses has broken through the historical highs year by year. With the advancement of science and technology, electric buses have gradually joined the operational fleet. The lack of renewal of the buses system has led to a decline in service levels. In the past, operators often set up the depot in the city center because of the cheap land, the power supply and other facilities required for the electric bus were often using previous experience selection, lacking overall systemic planning. T

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Chen, Hsin-Kai, and 陳信凱. "A Multi-Objective Genetic Approach for Planning Electric Vehicle Charging Station Location Problems with Dynamic Demands." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/23330551750412700878.

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碩士<br>中華大學<br>資訊工程學系碩士班<br>102<br>With rapid development of vehicles, demands of fossil fuel dramatic increasing while the total amount of fossil fuel on Earth dramatic decreasing. Moreover, the uses of fossil fuel increase the greenhouse effect and thus aid in heating Earth’s surface and atmosphere. It results from the fact that certain atmospheric gases, such as carbon dioxide, is able to change the energy balance of the planet by absorbing long wave radiation emitted from the Earth’s surface. In order to seek for alternative energy substitutes for fossil fuel, the development of electric ve

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Hsu, Chi-Wen, and 許琦汶. "The Location Selection of Advanced Life Support station for Two-Tiered Emergency Medical Services Systems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/77940682251842203395.

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碩士<br>國立嘉義大學<br>運輸與物流工程研究所<br>95<br>Many studies show that in our country there is a trend to increase of emergency medical services to turn out for work over the years, and the importance of emergency medical services appears to be steadily on the increase. For decrease the death and disability of advanced disease. It is the crucial whether first aider could arrive at the field soon and giving first aid treatment or not. The research utilizes the mathematical model to establish emergency medical services model and treats how to select optimum location from current facility as candidate points

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Book chapters on the topic "Charging station location selection"

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Singh, Sudhanshu Ranjan, Abhijeet K. Digalwar, and Srikanta Routroy. "Modelling Factors Influencing Charging Station Location Selection to Accelerate EV Adoption in India: An ISM-MICMAC Analysis." In Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-50204-0_32.

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Manjhi, Rampreet, Deepak Kumar Lal, Sandeep Biswal, and Surender Reddy Salkuti. "Optimal Location Selection of Electric Vehicle Charging Stations and Capacitors in Radial Distribution Networks Using GJO Algorithm." In Energy and Environmental Aspects of Emerging Technologies for Smart Grid. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-18389-8_31.

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Zhang, Yu, Xiangtao Liu, Tianle Zhang, and Zhaoquan Gu. "Review of the Electric Vehicle Charging Station Location Problem." In Communications in Computer and Information Science. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1304-6_35.

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Ács, Botond, and László Z. Varga. "Distributed Optimization of Charging Station Selection of Electric Vehicles." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70415-4_1.

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Karimanzira, Divas, and Helge Renkewitz. "Detection and localization of an underwater docking station in acoustic images using machine learning and generalized fuzzy hough transform." In Machine Learning for Cyber Physical Systems. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_3.

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AbstractLong underwater operations with autonomous battery charging and data transmission require an Autonomous Underwater Vehicle (AUV) with docking capability, which in turn presume the detection and localization of the docking station. Object detection and localization in sonar images is a very difficult task due to acoustic image problems such as, non-homogeneous resolution, non-uniform intensity, speckle noise, acoustic shadowing, acoustic reverberation and multipath problems. As for detection methods which are invariant to rotations, scale and shifts, the Generalized Fuzzy Hough Transfor

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Cai, Zongju, Xiran Sun, Yuming Liu, and Chao Xu. "Design of Charging Station System for Underwater High Energy Density Oxyhydrogen Fuel Cell." In Proceedings of the 10th Hydrogen Technology Convention, Volume 1. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8631-6_34.

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AbstractBased on the physical structure of the 20-foot container, this paper carries out the theoretical analysis of underwater charging station system about energy allocation of oxyhydrogen fuel cell and lithium batteries, and carries out the analysis of the equipment and components that have a great impact on the total weight of the charging station system, and summarizes the design principles to improve the energy density of the charging station system. The energy density of the underwater charging station is comprehensively improved in the aspects of technical design, material selection, s

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Pirolo, Luca, Pietro Belotti, Federico Malucelli, Rossella Moscarelli, and Paolo Pileri. "Optimal Charging Station Location in a Linear Cycle Path with Deviations." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60924-4_27.

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Chen, Ding, Min Zhou, Yutong Cui, Weijun Mao, Dawei Zhu, and Ying Wang. "Location of Electric Vehicle Charging Station Based on Particle Swarm Optimization." In The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89511-2_127.

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Giménez, Juan F., Amparo López-Vicente, Carol Soriano, Raquel Marzo, José Solaz, and Elisa Signes. "Stations of the Future: A Study on EV Charging Stations Considering Users’ Requirements and Expectations." In Lecture Notes in Mobility. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89444-2_3.

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Abstract One of the products included in USER-CHI project is the definition of the charging stations that not only EVs and LEVs require, but also fulfil the needs and expectations of the end users. A qualitative and quantitative user research following the user experience principles have been performed, achieving a deep knowledge of EV drivers’ charging preferences and patterns in order to increase their acceptance. As a result of this research, we have identified basic requirements, increasing value and desirable features that are related to the charging process of an EV, that should be inclu

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Gonçalves, Catarina, Ângela Silva, and Helena Sofia Rodrigues. "Location of an Electric Vehicle Charging Station: Demographic Factor as Decision Making." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53025-8_34.

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Conference papers on the topic "Charging station location selection"

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Shen, Wenjia, Bo Zhou, Ruiwei Jiang, and Siqian Shen. "Sequential Charging Station Location Optimization under Uncertain Charging Behavior and User Growth." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10885967.

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Yue, Caitong, Lihong Cheng, Jing Liang, Kunjie Yu, and Mengmeng Li. "Multimodal Multiobjective Optimization in the Charging Station Site Selection." In 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025. https://doi.org/10.1109/cec65147.2025.11042920.

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Govind, Digambar Singh, and Manoj Fozdar. "Optimal Location and Impact Analysis of Fast Charging Station on Distribution System." In 2024 IEEE 11th Power India International Conference (PIICON). IEEE, 2024. https://doi.org/10.1109/piicon63519.2024.10995091.

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Wang, Yunfeng, Xinzhang Wu, and Zhuangzhuang Li. "Optimization of Charging Station Location Based on Improved Particle Swarm Optimization Algorithm." In 2025 International Conference on Digital Analysis and Processing, Intelligent Computation (DAPIC). IEEE, 2025. https://doi.org/10.1109/dapic66097.2025.00014.

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Quan, Wei, Qipeng Zheng, Wenxuan Ji, and Feng Li. "Research on Improving Sparrow Search Algorithm for Charging Station Site Selection." In 2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE, 2024. http://dx.doi.org/10.1109/cisce62493.2024.10653364.

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Chandra, Isha, Apramay Singh, Navneet Kumar Singh, Paulson Samuel, Om Hari Gupta, and Asheesh Kumar Singh. "Hybrid PSO-based Optimal Location of Electric Vehicle Charging Station in Distribution Networks." In 2024 IEEE Students Conference on Engineering and Systems (SCES). IEEE, 2024. http://dx.doi.org/10.1109/sces61914.2024.10652265.

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Zheng, Qipeng, Feng Li, Wenxuan Ji, and Wei Quan. "Research on Charging Station Site Selection Based on Immune Particle Swarm Algorithm." In 2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE, 2024. http://dx.doi.org/10.1109/cisce62493.2024.10653128.

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Moghaddas-Tafreshi, Seyed-Masoud, Payam Farhadi, and Mehdi Kavkar Mehdikhanmahaleh. "A Novel Blockchain-Based Model for Automotive Selection of an Electric Vehicle Charging Station." In 2025 10th International Conference on Technology and Energy Management (ICTEM). IEEE, 2025. https://doi.org/10.1109/ictem66196.2025.11063503.

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Li, Jianqiao, Qili Zhang, Xiaochen Wang, and Na Geng. "The Location and Capacity Optimization of Public Charging Station based on Adaptive Large Neighborhood Search Algorithm." In 2025 IEEE 3rd International Conference on Power Science and Technology (ICPST). IEEE, 2025. https://doi.org/10.1109/icpst65050.2025.11089084.

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Shao, Wenhan, Yan Jiang, Feng Zhao, et al. "A Local Search Algorithm Leveraging the Reasoning Abilities of Large Language Models for Solving Urban Charging Station Location Problem." In 2025 2nd International Conference on Smart Grid and Artificial Intelligence (SGAI). IEEE, 2025. https://doi.org/10.1109/sgai64825.2025.11009651.

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Reports on the topic "Charging station location selection"

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Powell, Bonnie, and Caley Johnson. Impact of Electric Vehicle Charging Station Reliability, Resilience, and Location on Electric Vehicle Adoption. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2432350.

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