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1
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 (December 14, 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 cost. The method uses the GCN to extract charging stations. The charging demand of each candidate station is calculated through the traffic flow information to optimize the location of charging stations. Finally, the cost of the charging station network is evaluated. A case study on charging station selection shows that the method can solve the EV charging station location problem.
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Zhao, Shu Qiang, and Zhi Wie Li. "The Optimization Model of Planning Electric Vehicle Charging Station." Applied Mechanics and Materials 672-674 (October 2014): 1183–88. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1183.
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Aiming at the problem of electric vehicle charging station planning, the clients of fast charging stations is analyzed. The optimal mathematical model about siting of electric vehicle charging stations is proposed based on the city's geographic information. We obtain the optimal location of charging stations by charging convenient factor as a constraint. And divide the load area which is served by each charging station by the Voronoi. According to the load which is served by each charging station, this paper designs the optimal battery charger number of each charging station with the Queuing Theory. Finally, optimize the charging convenient factor using the total cost as objective function. The analysis of examples verifies the effectiveness and the practicability of the proposed planning approach.
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Spuritha, M., Harshitha Damineni, Shreemayi Sonti, Veshala Lokesh Kumar, Siri Chandana Veeramalla, Ramprasad Kokkula, and D. Indira. "Crowd sourced smart EV charging station network using ML." E3S Web of Conferences 309 (2021): 01097. http://dx.doi.org/10.1051/e3sconf/202130901097.
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Electric vehicle owners face the problem of having limited charging station options. Individual charging stations near households can act as a viable solution to solve this problem. A forecasting model which can effectively predict the power consumption of a charging station will help charging station owners get a clear view of how much energy to produce.With this intent, this paper proposes an Internet of Things (IoT) based charging station network that acts as a platform to provide charging to electric vehicles and a model based on ARIMA whose learners are fitted to the charging station subsets with optimum parameters to increase the overall performance of sales prediction. The proposed model predicted power consumption for 7 charging stations, with average MAPE, RMSE and R2 values of 12.88%, 5.67, and 0.79 respectively.
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Ademulegun, Oluwasola O., Paul MacArtain, Bukola Oni, and Neil J. Hewitt. "Multi-Stage Multi-Criteria Decision Analysis for Siting Electric Vehicle Charging Stations within and across Border Regions." Energies 15, no. 24 (December 12, 2022): 9396. http://dx.doi.org/10.3390/en15249396.
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Electric Vehicles (EVs) replace fossil fuel vehicles in effort towards having more sustainable transport systems. The battery of an EV is recharged at a charging point using electricity. While some recharging will be required at locations where vehicles are normally parked, other recharging could be necessary at strategic locations of vehicular travel. Certain locations are suitable for EV charging station deployment, others are not. A multi-stage decision analysis methodology for selecting suitable locations for installing EV charging station is presented. The multi-stage approach makes it possible to select critical criteria with respect to any defined objectives of the EV charging station and techno-physio-socio-economic factors without which the EV charging station could not be deployed or would not serve its designated purpose. In a case, the type of charging station is specified, and a purpose is defined: rapid EV charging stations intended for public use within and across border regions. Applied in siting real EV charging stations at optimal locations, stages in the methodology present additional techno-physio-socio-economic factors in deploying the type of EV charging stations at optimal locations and keep the EV charging stations operating within acceptable standards. Some locations were dropped at the critical analysis stage; others were dropped at the site-specific analysis stage and replacement sites were required in certain instances. Final locations included most optimal, less optimal, least optimal, and strategic or special need locations. The average distances between contiguous recharging locations were less than 60 miles. Using any specified separation standard, the number of additional EV charging stations required between EV charging stations were determinable with the Pool Box. The Overall Charging Station Availability quadrants suggest that the overall user experience could get worse as less-standardized additional EV charging stations are deployed.
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., Lakshmi, Malini K V, Likitha N E, Basavaraj M, Vanfana K, and Varun Gowda. "Smart Self Monitoring Eco Friendly EV Charging Station." International Journal of Innovative Research in Information Security 09, no. 03 (June 23, 2023): 229–33. http://dx.doi.org/10.26562/ijiris.2023.v0903.32.
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Due to their low expenses for operation and commitment to the environment, electric cars (EVs) are growing in popularity. However, the inadequate charging infrastructure limits their popularity. To keep their vehicles always ready for use, EV owners need access to convenient and dependable charging stations. Thus, promoting the adoption of EVs requires the installation of electric charging stations. A specialized infrastructure called an electric charging station is created to supply electricity to electric vehicles. It is made up of a unit for charging, one for distributing power, and one for communicating. The charging unit is in charge of feeding electricity from the grid to an electric vehicle's battery. The electric car receives power from the charging unit through the power distribution unit. To make sure that the charging process is secure, dependable, and effective, the communication unit is in charge of maintaining communication between the charging station and the electric car. There are two categories of electric charging stations: DC rapid charging stations and AC charging stations. While DC fast charging stations offer a faster charging rate of up to 350 kW, AC charging stations offer a slower rate of up to 22 kW. Although installing DC fast charging stations costs more money, they are essential for long- distance travel and in places where there is a high demand for quick charging.
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Mishra, Partha, Eric Miller, Shriram Santhanagopalan, Kevin Bennion, and Andrew Meintz. "A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles." Energies 15, no. 10 (May 21, 2022): 3788. http://dx.doi.org/10.3390/en15103788.
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Widespread adoption of heavy-duty (HD) electric vehicles (EVs) will soon necessitate the use of megawatt (MW)-scale charging stations to charge high-capacity HD EV battery packs. Such a station design needs to anticipate possible station traffic, average and peak power demand, and charging/wait time targets to improve throughput and maximize revenue-generating operations. High-power direct current charging is an attractive candidate for MW-scale charging stations at the time of this study, but there are no precedents for such a station design for HD vehicles. We present a modeling and data analysis framework to elucidate the dependencies of a MW-scale station operation on vehicle traffic data and station design parameters and how that impacts vehicle electrification. This framework integrates an agent-based charging station model with vehicle schedules obtained through real-world vehicle telemetry data analysis to explore the station design and operation space. A case study applies this framework to a Class 8 vehicle telemetry dataset and uses Monte Carlo simulations to explore various design considerations for MW-scale charging stations and EV battery technologies. The results show a direct correlation between optimal charging station placement and major traffic corridors such as cities with ports, e.g., Los Angeles and Oakland. Corresponding parametric sweeps reveal that while good quality of service can be achieved with a mix of 1.2-megawatt and 100-kilowatt chargers, the resultant fast charging time of 35–40 min will need higher charging power to reach parity with refueling times.
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Zhang, Peipei, Juan Chen, Lilan Tu, and Longteng Yin. "Layout Evaluation of New Energy Vehicle Charging Stations: A Perspective Using the Complex Network Robustness Theory." World Electric Vehicle Journal 13, no. 7 (July 12, 2022): 127. http://dx.doi.org/10.3390/wevj13070127.
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At present, the new energy vehicle industry is developing rapidly, but the relative lag in the development of its supporting infrastructure, especially charging stations, has become a bottleneck that restricts the development of the electric vehicle industry. In this paper, we propose a model for constructing a network of new energy vehicle charging facilities based on complex network theory and analyze the operation and the rationality of the layout of the new energy vehicle (NEV) charging stations in Wuhan and Hangzhou, respectively. The results show that the current layout of new energy vehicle charging stations in the city is relatively reasonable, but the allocation of charging pile resources is unreasonable. Our results of the virtual charging station network constructed by adding new charging station nodes show that the change in network structure helps to enhance the performance of the charging station system.
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Shi, Qing Sheng, and Yi Cao. "Gaussian Mixture Model Clustering Based Optimal Location of EV Charging Stations." Applied Mechanics and Materials 380-384 (August 2013): 3400–3403. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3400.
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Building enough charging stations is the only way to let new energy vehicles come into our daily life. While, the cost of building a charging station is very expensive. Therefore, spatial optimal location of charging stations has to be dealt with. The main purpose of this paper is to investigate the spatial optimal location of charging stations using Gaussian Mixture Model clustering and charging requirement spots are taken as the clustering benchmark. The clustering procedure of charging station spatial optimal location is programmed using m-language. Finally, simulation results show the validity of proposed method.
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Răboacă, Maria-Simona, Irina Băncescu, Vasile Preda, and Nicu Bizon. "An Optimization Model for the Temporary Locations of Mobile Charging Stations." Mathematics 8, no. 3 (March 21, 2020): 453. http://dx.doi.org/10.3390/math8030453.
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A possible solution with which to alleviate the range anxiety of electric vehicle (EV) drivers could be a mobile charging station which moves in different places to charge EVs, having a charging time of even half an hour. A problem that arises is the impossibility of charging in any location due to heavy traffic or limited space constraints. This paper proposes a new operational mode for the mobile charging station through temporarily stationing it at different places for certain amounts of time. A mathematical model, in the form of an optimization problem, is built by modeling the mobile charging station as a queuing process, the goal of the problem being to place a minimum number of temporary service centers (which may have one or more mobile charging stations) to minimize operating costs and the charger capacity of the mobile charging station so that the service offered is efficient. The temporary locations obtained are in areas with no or few fixed charging stations, making the mobile station infrastructure complementary to the fixed charging station infrastructure. The temporary location operational mode, compared to current moving operational mode, is more efficient, having a small miss ratio, short mean response time and short mean queuing time.
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El-fedany, Ibrahim, Driss Kiouach, and Rachid Alaoui. "System architecture to select the charging station by optimizing the travel time considering the destination of electric vehicle drivers in smart cities." Bulletin of Electrical Engineering and Informatics 9, no. 1 (February 1, 2020): 273–83. http://dx.doi.org/10.11591/eei.v9i1.1564.
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The main limitations of electric vehicles are the limited scope of the battery and their relatively long charging times. This may cause discomfort to drivers of electric vehicles due to a long waiting period at the service of the charging station, during their trips. In this paper, we suggest a model system based on argorithms, allowing the management of charging plans of electric vehicles to travel on the road to their destination in order to minimize the duration of the drivers' journey. The proposed system decision to select the charging station, during advance reservation of electric vehicles, take into account the time of arrival of electric vehicles at charging stations, the expected charging time at charging stations, the local status of the charging stations in real time, and the amount of energy sufficient for the electric vehicle to arrive at the selected charging station. Furthermore, the system periodically updates the electric vehicule reservations to adjust their recharge plans, when they reach their selected earlier station compared to other vehicules requesting new reservations, or they may not arrive as they were forecast, due to traffic jams on the road or certain reluctance on the part of the driver.
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Wang, Zhen Po, Peng Liu, Hai Bin Han, Chun Lu, and Tao Xin. "A Distribution Model of Electric Vehicle Charging Station." Applied Mechanics and Materials 44-47 (December 2010): 1543–48. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.1543.
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The location and the overall arrangement of the charging stations is an important problem with the development of electric vehicles. It is related to the charging needs, city planning, service level of charging station, geographic location and competitive ability and so on. A distribution model of EV charging station is introduced in the paper. In order to describe the model preferably, this paper introduces the attractive factor of charging stations and the area-different factor. The model can give the charging station rational positions by analyzing the data of the traffic flow and the electric-consuming-rate of cars on the road. A case study is given to illustrate the applying the model.
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Zhao, Yuting, and Chen Li. "Design of Charging Station Information Monitoring System based on CAT.1." Scientific Journal of Technology 5, no. 6 (June 20, 2023): 16–21. http://dx.doi.org/10.54691/sjt.v5i6.5156.
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Intelligent charging station information monitoring system is significant to the construction of intelligent charging stations. A charging station information monitoring system is designed based on 4G CAT.1. Sensors are used to detect different information like electricity usage and positioning. A rely is also used to control the charging station by receiving remote control signal from cloud platform. After debugging, the system can realize the remote information monitoring.
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Shi, Liu, Liao, Niu, Ibrahim, and Fu. "An Electric Taxi Charging Station Planning Scheme Based on an Improved Destination Choice Method." Energies 12, no. 19 (October 5, 2019): 3781. http://dx.doi.org/10.3390/en12193781.
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The environmental crisis has prompted the development of electric vehicles as a green and environmentally friendly mode of travel. Since a reasonable layout of electric vehicle (EV) charging stations is the prerequisite for developing the EV industry, obtaining an optimal and efficient EV charging station planning scheme is a key issue. Although the Chinese government has carried out a plan to build EV charging piles in residential and working places, it cannot properly fulfill the task of matching the charging needs for public transportation vehicles such as electric taxis (ETs). How to evaluate the performance of fast charging stations (FCSs) and how to help find the optimal ET charging station planning scheme are new challenges. In this paper, an improved destination selection model is proposed to simulate the ET operation system and to help find the optimal ET charging station size with statistical analysis based on the charging need prediction. A numerical case study shows that the proposed method can address ET charging behavior well and can help to statistically determine the size of each ET charging station, which should satisfy the constraints on the preset proportion of the ET charging service requests.
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Bhattacharya, Purnendu, Asif Ali, Indrajit Mondal, and Prof Partha Sarathi Bose. "Design and Model Making of Electric Vehicle Charging Station." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 2230–32. http://dx.doi.org/10.22214/ijraset.2023.52026.
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Abstract: An EV charging station is a facility designed to supply electric power for charging electric vehicles (EVs). As the demand for EVs continues to grow due to their environmental benefits and cost savings, the demand for EV charging stations is increasing rapidly. This paper provides an abstract for an EV charging station, covering topics such as the different types of EV charging stations, their working principles, the importance of charging infrastructure, and the benefits of using EVs. The paper also discusses the challenges associated with the development and deployment of EV charging stations, including their cost, availability of charging points, and the need for standardization. Furthermore, the paper presents some possible solutions to overcome these challenges, such as promoting government incentives, adopting innovative technologies, and increasing collaboration among industry stakeholders. Overall, the paper provides an insightful overview of EV charging stations, highlighting the importance of these facilities for the widespread adoption of EVs and the transition to a sustainable transportation system.
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Wolbertus, Rick, and Bas Gerzon. "Improving Electric Vehicle Charging Station Efficiency through Pricing." Journal of Advanced Transportation 2018 (September 3, 2018): 1–11. http://dx.doi.org/10.1155/2018/4831951.
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Recent studies show that charging stations are operated in an inefficient way. Due to the fact that electric vehicle (EV) drivers charge while they park, they tend to keep the charging station occupied while not charging. This prevents others from having access. This study is the first to investigate the effect of a pricing strategy to increase the efficient use of electric vehicle charging stations. We used a stated preference survey among EV drivers to investigate the effect of a time-based fee to reduce idle time at a charging station. We tested the effect of such a fee under different scenarios and we modelled the heterogeneity among respondents using a latent class discrete choice model. We find that a fee can be very effective in increasing the efficiency at a charging station but the response to the fee varies among EV drivers depending on their current behaviour and the level of parking pressure they experience near their home. From these findings we draw implications for policy makers and charging point operators who aim to optimize the use of electric vehicle charging stations.
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Hu, Haoxuan, and Yuchen Zhang. "An Empirical Research of the Mechanism from Electric Vehicle Production to Charging Station R&D in China." Processes 9, no. 8 (August 15, 2021): 1407. http://dx.doi.org/10.3390/pr9081407.
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Electric vehicles (EVs) are regarded as an effective method for dealing with serious environmental pollution. The Chinese government has implemented a series of incentives to accelerate the promotion of EV. However, the increasing production of EVs gives rise to a greater demand for better quality charging station. This study aimed to certify the impact of the production of EVs on charging station research and development (R&D) in China, with mediating effect methods and a panel fixed effect model. The conclusions derived from the study were: (1) Statistically, the production of EVs positively and significantly impacts charging station R&D; (2) the mediating role of investment in charging stations is verified in the relationship between the production of EVs and charging station R&D; (3) environmental tax can moderate the relationship between the production of EVs and charging station R&D. These results implicate, for the first time, that the production of EVs can enhance charging station R&D through the mediating role of charging station investments and the moderating role of environmental tax.
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Wang, Jianxue, Yanlin Cui, and Minghui Zhu. "Probabilistic Harmonic Calculation in Distribution Networks with Electric Vehicle Charging Stations." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/167565.
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Integrating EV charging station into power grid will bring impacts on power system, among which the most significant one is the harmonic pollution on distribution networks. Due to the uncertainty of the EV charging process, the harmonic currents brought by EV charging stations have a random nature. This paper proposed a mathematical simulation method for studying the working status of charging stations, which considers influencing factors including random leaving factor, electricity price, and waiting time. Based on the proposed simulation method, the probability distribution of the harmonic currents of EV charging stations is obtained and used in the calculation of the probability harmonic power flow. Then the impacts of EVs and EV charging stations on distribution networks can be analyzed. In the case study, the proposed simulation and analysis method is implemented on the IEEE-34 distribution network. The influences of EV arrival rates, the penetration rate, and the accessing location of EV charging station are also investigated. Results show that this research has good potential in guiding the planning and construction of charging station.
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Zhang, Bo, Bicheng Huang, and Zhongxian Wang. "Study on Capacity Distribution of Optimal Configuration Ratio of Urban Replenishment Station of Electric Vehicles." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 1 (February 20, 2020): 119–25. http://dx.doi.org/10.2174/1874476105666190830111228.
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Background: This paper deeply studies the influence of the capacity distribution of urban charging and replacing power stations on the distribution network and gives the optimal solution. Objective: The optimal configuration scheme of the charging and replacing station has been given to reduce the impact of the charging and replacing station on the distribution network. Methods: First, the Monte Carlo simulation method is used to extract the influencing factors. The probability load models of the battery replacement station, the slow charging station and the fast charging station are established respectively. The capacity distribution is represented by three different types of charging and switching station configuration ratios. Furthermore, the impact of the charging and replacing power station on the economics and safety of the distribution network is analyzed. Different from other literature, the “peak-filling” model with “minimum peak load”, “maximum valley load” and “minimum peak-to-valley difference” is established, and then PSO is adopted. Results: Finally, the actual configuration is used to compare and analyze the four configuration schemes to prove the superiority of the optimization scheme. Conclusion: Three models have different key influencing factors, so that the electric vehicle load forecasting is more targeted and accurate. The results show that more battery replacement stations can reduce the impact of EV charging on the distribution network, and the construction of the supply replenishment should be based on the construction of the power station.
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Niu, Liyong, and Di Zhang. "Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization." Scientific World Journal 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/354952.
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Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly.
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Deokate, Er Ashwini, Vrushali Patil, Raunak Sirsam, Vidisha Sondawale, Ajay Hedau, and Abhishek Gupta. "A Literature Survey Paper on Electric Vehicle Charging Station Finder App." International Journal for Research in Applied Science and Engineering Technology 11, no. 2 (February 28, 2023): 579–80. http://dx.doi.org/10.22214/ijraset.2023.49089.
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Abstract: In today's era, EV vehicles are being seen more and more. This is the coming future that most of the vehicles are going to remain electric vehicles. According to this we will get to see mostly EV charging stations. The electric car driver will mostly take the car to the charging station itself for charging. So we are making an app for EV rider which will help to find EV charging station and book charging slot. This app will show all the stations around the rider. Rider can easily access any station information. Like whether there is a slot available at the charging station or not, the rider will know on the app. And rider can book charging slot from this app, they can book charging slot at particular time or any date. And the rider can pay the payment through this. With the help of this app, the rider can save his time and get the right information and stay updated User can use this app easily and improve your journey.
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Shi, Qing Sheng, and Xiao Zhen Zheng. "Electric Vehicle Charging Stations Optimal Location Based on Fuzzy C-Means Clustering." Applied Mechanics and Materials 556-562 (May 2014): 3972–75. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3972.
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As plug-in hybrid electric vehicles and battery electric vehicle ownership is expanding, there is a growing need for widely distributed publicly accessible charging stations. Building a charging station cost too much. Therefore, optimal location of charging stations has to be dealt with. The main purpose of this paper is to investigate the optimal location of charging stations using fuzzy C-means clustering method. Preliminary of fuzzy C-means clustering method is introduced first followed by the procedure of charging station optimal location using Fuzzy C-means Clustering. Finally, simulation results show the validity of proposed method.
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Nishimwe H., Leon Fidele, and Sung-Guk Yoon. "Combined Optimal Planning and Operation of a Fast EV-Charging Station Integrated with Solar PV and ESS." Energies 14, no. 11 (May 28, 2021): 3152. http://dx.doi.org/10.3390/en14113152.
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Sufficient and convenient fast-charging facilities are crucial for the effective integration of electric vehicles. To construct enough fast electric vehicle-charging stations, station owners need to earn a reasonable profit. This paper proposed an optimization framework for profit maximization, which determined the combined planning and operation of the charging station considering the vehicle arrival pattern, intermittent solar photovoltaic generation, and energy storage system management. In a planning horizon, the proposed optimization framework finds an optimal configuration of a grid-connected charging station. Besides, during the operation horizon, it determines an optimal power scheduling in the charging station. We formulated an optimization framework to maximize the expected profit of the station. Four types of costs were considered during the planning period: the investment cost, operational cost, maintenance cost, and penalties. The penalties arose from vehicle customers’ dissatisfaction associated with waiting time in queues and rejection by the station. The simulation results showed the optimal investment configuration and daily power scheduling in the charging station in various environments such as the downtown, highway, and public stations. Furthermore, it was shown that the optimal configuration was different according to the environments. In addition, the effectiveness of solar photovoltaic, energy storage system, and queue management was demonstrated in terms of the optimal solution through a sensitivity analysis.
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Bachiri, Khalil, Ali Yahyaouy, Hamid Gualous, Maria Malek, Younes Bennani, Philippe Makany, and Nicoleta Rogovschi. "Multi-Agent DDPG Based Electric Vehicles Charging Station Recommendation." Energies 16, no. 16 (August 19, 2023): 6067. http://dx.doi.org/10.3390/en16166067.
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Electric vehicles (EVs) are a sustainable transportation solution with environmental benefits and energy efficiency. However, their popularity has raised challenges in locating appropriate charging stations, especially in cities with limited infrastructure and dynamic charging demands. To address this, we propose a multi-agent deep deterministic policy gradient (MADDPG) method for optimal EV charging station recommendations, considering real-time traffic conditions. Our approach aims to minimize total travel time in a stochastic environment for efficient smart transportation management. We adopt a centralized learning and decentralized execution strategy, treating each region of charging stations as an individual agent. Agents cooperate to recommend optimal charging stations based on various incentive functions and competitive contexts. The problem is modeled as a Markov game, suitable for analyzing multi-agent decisions in stochastic environments. Intelligent transportation systems provide us with traffic information, and each charging station feeds relevant data to the agents. Our MADDPG method is challenged with a substantial number of EV requests, enabling efficient handling of dynamic charging demands. Simulation experiments compare our method with DDPG and deterministic approaches, considering different distributions and EV numbers. The results highlight MADDPG’s superiority, emphasizing its value for sustainable urban mobility and efficient EV charging station scheduling.
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Huang, Yongyi, Atsushi Yona, Hiroshi Takahashi, Ashraf Mohamed Hemeida, Paras Mandal, Alexey Mikhaylov, Tomonobu Senjyu, and Mohammed Elsayed Lotfy. "Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation." Sustainability 13, no. 11 (May 30, 2021): 6163. http://dx.doi.org/10.3390/su13116163.
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Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues.
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Ye, Bo, Zhang Zhou He, Guo Meng Huang, Xue Song He, and Hui Quan Li. "The Study and Design of Electric System for Photovoltaic Generation Mix Charging Station." Applied Mechanics and Materials 291-294 (February 2013): 2362–65. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2362.
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With the development of electric vehicle industry, it is necessary to construct more electric vehicle charging stations to promote the popularization of electric vehicles. As photovoltaic generation owns flexible installing, convenient power supplying, and environmental protecting characteristics, it is suitable for providing power for electric vehicle charging stations and reducing a network loads. After analyzed electric vehicle charging demand, this paper proposed the designing concept of the electric system for the photovoltaic generation mix charging station, which was based on the battery charging and discharging characteristics as well as its usage. Then, the paper provided a selection of electric equipments for the charging station and an electric wiring diagram after designing the electric system. This study and design may help for promoting construction of electric vehicle charging stations, and development and popularization of electric vehicles.
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Sun, Yinghan, Jiangbo Wang, Cheng Li, and Kai Liu. "Competitiveness Evaluation of Electric Bus Charging Services Based on Analytic Hierarchy Process." World Electric Vehicle Journal 13, no. 5 (May 9, 2022): 81. http://dx.doi.org/10.3390/wevj13050081.
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The premise of the large-scale operation of electric buses corresponds to efficient charging service guarantees. Recent research on charging stations mainly aims to obtain the construction location and construction sequence through optimization methods or decision-making methods. This research has considered the aspects of geography, charging efficiency, economic efficiency, and emergency response capacity. The increase of charging stations will lead to competition among charging stations, unbalanced use of charging facilities, and unnecessary loss of electricity to the power grid. In fact, few studies pay attention to the actual operation of existing charging stations. Therefore, it is necessary to establish a scientific, comprehensive, and efficient charging services evaluation framework to support the actual operation of charging stations. Based on the analytic hierarchy process (AHP), this paper designs a multi-level indicator evaluation framework, which includes 6 first-level indicators and 20 s-level indicators. The first-level indicators are cutting peak and filling valley (A1), location and scale (A2), intelligent technology (A3), equipment efficiency (A4), operating income (A5), and reliability (A6). Through the questionnaire survey of ten experts in related fields, we understood the importance and attention of these indicators. The results show that the weights of indicators of location and scale index (A2) and reliability (A6) are high, which are 0.2875 and 0.2957, respectively. The least concerned indicator is equipment utilization efficiency (A4), at a weight of 0.0531. According to the actual data of charging stations in Zhengzhou, China, the comprehensive competitiveness of several charging stations is evaluated by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The result shows that station 1 has the highest comprehensive competitiveness, followed by station 2 and station 7. The evaluation framework proposed in this paper comprehensively considers a variety of factors. The combination of AHP and TOPSIS can reduce the uncertainty in experts’ evaluation of the service of the charging station.
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Chen, Guang, Zhuo Ran Song, Pan Dai, Yang Liu, and Yong Ma. "Study on Multi-Objective Optimal Planning of Electric Vehicle Charging Stations with Alternative Sites." Advanced Materials Research 1070-1072 (December 2014): 1656–63. http://dx.doi.org/10.4028/www.scientific.net/amr.1070-1072.1656.
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Planning of charging stations for electric vehicles (EVs) is the foundation of EV’s promotion and development. A novel multi-objective optimization model is proposed in this paper to better locate and size the charging stations for EVs from given alternative sites. Economic costs of charging station and the time wasted in waiting for charging are minimized in the model. The capacity constraints of the charging stations are included as main constraints. Pareto front is used to compare and estimate the practical value of the current substation locating and sizing plans. A calculation method based on rasterization and Voronoi diagram is proposed to make it clear where the jurisdiction of each charging station ends. Finally, the proposed model and calculation method are verified using case study.
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D Dhana Prasad and R Ramprasanth. "Modeling and Control of a Multiport Converter based EV Charging Station with PV and Battery." International Journal for Modern Trends in Science and Technology 7, no. 03 (April 9, 2021): 95–100. http://dx.doi.org/10.46501/ijmtst0703017.
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As an environmental friendly vehicle, the increasing number of electrical vehicles (EVs) leads to a pressing need of widely distributed charging stations, especially due to the limited on-board battery capacity. However, fast charging stations, especially super-fast charging stations may stress power grid with potential overload at peaking time, sudden power gap and voltage sag. This project discusses the implementation and modeling of space vector modulation to multiport converter based EV charging station integrated with PV power generation, and battery energy storage system. In this paper, the control scheme and combination of PV power generation, EV charging station, and battery energy storage (BES) provides improved stabilization including power gap balancing, peak shaving and valley filling, and voltage sag compensation. As a result, the influence on power grid is reduced due to the matching between daily charging demand and adequate daytime PV generation. Simulation results are presented to confirm the benefits at different modes of this proposed multiport EV charging circuits with the PV-BES configuration with SVM technique. Furthermore, SiC devices are employed to the EV charging station to further improve the efficiency.
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Jan, Semjon, Grexa Ján, and Mako Peter. "DESIGN OF DOCKING SYSTEM FOR MOBILE ROBOTICS PLATFORM TYPE AGV." TECHNICAL SCIENCES AND TECHNOLOGIES, no. 4 (14) (2018): 210–15. http://dx.doi.org/10.25140/2411-5363-2018-4(14)-210-215.
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Urgency of the research. Automatic battery charging of AGV platforms allows you to maximize their potential. Safe and quickly positioning AGVs in a charging station equipped with appropriate contacts, reduces the charging time as well as the purchase price of the device. Target setting. The aim of the solution is to design an automatic docking and charging station from a used hand-held charging station. In the design, it was necessary to ensure the appropriate position of the AGV platform against the docking station. Actual scientific researches and issues analysis. The issue of fast and reliable charging of mobile service robots is highly up-to-date. The reason for this is the growing deployment of AGV platforms in various industrial or service sectors. Uninvestigated parts of general matters defining. This article focuses on a specific solution for the provision of transport services. Transport services come from the need to transport medical supplies and medications in a multi-storey hospital building. The movement of the robot between the floors is solved by the use of lifts used by the personal of hospital. The research objective. The aim of the research was to design a docking and charging station utilized an already purchased power-up charger. The design was aimed at creating an appropriate power transmission system between the charger and the AGV platform batteries. The price ceiling for the whole facility was worth € 2,000. The statement of basic materials. The use of docking and charging stations for mobile service robots is dependent on a number of parameters. In particular, the parameters depend on the area of use, the size of the battery to be charged, and the amount of robots being recharged at the station. Last but not least, charging time and purchase price are also important. Conclusions. The task of the solution was to design a docking station design for the AGV platform. At the beginning, three variants were created, from which the most appropriate solution was chosen using the scoring method. However, before designing the docking station design, it was necessary to modify the existing AGV platform construction so that it could be connected to the docking station charging mechanism. The design of the docking station itself consisted of the design of the charging and charging mechanism. These mechanisms provide charge and guidance of the AGV platform to the docking station. Mechanisms are not dependent on each other, since the charging mechanism is activated later than the drive mechanism. Subsequently, a design of the docking station, which can be anchored to the floor or to the wall, was created. At the docking station there is a charger from Hoppecke, which provides the AGV platform charging. The design dimensions of the docking station have been greatly influenced by the size of the above-mentioned charger. It has been found that new and better technologies will not be needed at the docking stations in the future, as AGV platforms can be guided without their help. The development of new and better quality systems will bring new guidance options to AGV platforms and docking stations.
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Ullah, Irfan, Kai Liu, Safa Bhar Layeb, Alessandro Severino, and Arshad Jamal. "Optimal Deployment of Electric Vehicles’ Fast-Charging Stations." Journal of Advanced Transportation 2023 (April 3, 2023): 1–14. http://dx.doi.org/10.1155/2023/6103796.
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As climate change has become a pressing concern, promoting electric vehicles’ (EVs) usage has emerged as a popular response to the pollution caused by fossil-fuel automobiles. Locating charging stations in areas with an expanding charging infrastructure is crucial to the accessibility and future success of EVs. Nonetheless, suitable planning and deployment for EV fast-charging stations is one of the most critical determinants for large-scale EV adoption. Installing charging stations in existing fuel/gas stations in the city may be an effective way to persuade people to adopt EVs. In this paper, we aim to optimally locate a fast-charging station in an existing gas station in the real-world scenario of Aichi Prefecture, Japan. The purpose is to locate and size fast-charging stations in such ways that drivers can get access to these charging facilities within a rational driving range while considering real-world constraints. Furthermore, we include the investment cost and the EVs users' convenience cost. This problem is formulated by five integer linear programming using a weighted set covering models. The developed model determines where to locate charging stations as well as how many chargers should be installed in each charging station. The experimental results demonstrate that an appropriate location scheme can be obtained using the model M 5 . A computational experiment identifies the best infrastructure solutions for policymakers to consider in the context of growing environmental policies.
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ÇAKMAK, Recep, and Abdullah TURAN. "Electric Vehicle Charging Station Infrastructure on the Basis of Provinces in Turkey: Analysis through the Metrics." Karadeniz Fen Bilimleri Dergisi 12, no. 1 (June 15, 2022): 246–68. http://dx.doi.org/10.31466/kfbd.1029677.
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The fact that fossil fuels are exhaustible and harmful to the environment, the goals of constituting a sustainable and cleaner environment, and developments in battery technologies have led to a tendency towards electric vehicles instead of the vehicles which have traditional internal combustion engines working with fossil fuels. Especially in the last five years, electric vehicle (EV) sales have increased, and this increase is expected to continue increasing in the coming years. The increasing number of electric vehicles leads to the need for EV charging stations. To make strategic plans, to guide investors and to provide the appropriate infrastructure for the electric vehicle customers, the infrastructure of electric vehicle charging stations in each region needs to be analyzed in detail. In this study, the quantitative situation of the electric vehicle charging station infrastructure on the basis of provinces in Turkey as of the end of 2020 is discussed and two new metrics which use to evaluate EV charging station infrastructure are proposed. In this context, the EV charging station status is presented with tables and infographic maps through the metrics in the literature used in the evaluation of the EV charging station infrastructure and the metrics proposed in this study. 81 provinces of Turkey are compared and presented in terms of EV charging station infrastructure through the metrics. It is foreseen that the obtained and presented findings in this study will be beneficial to electric vehicle customers, electric vehicle charging station investors, the government and other public institutions that could be developed the strategy to increase the proliferation of electric vehicles. In addition, this publication might be used as a reference study to track the pace of improvements in the EV charging station infrastructure and to compare the improvements with 2020.
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Lu, Shixiang, Xiaofeng Feng, Guoying Lin, Jiarui Wang, and Qingshan Xu. "Non-Intrusive Load Monitoring and Controllability Evaluation of Electric Vehicle Charging Stations Based on K-Means Clustering Optimization Deep Learning." World Electric Vehicle Journal 13, no. 11 (October 25, 2022): 198. http://dx.doi.org/10.3390/wevj13110198.
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Electric vehicles have the advantages of zero emissions and high energy efficiency. They have a broad potential in today’s social life, especially in China where they have been widely used. In the current situation, whereby the storage capacity of electric vehicles is continually increasing and the requirements for grid stability are getting higher and higher, V2G technology emerges to keep up with the times. Since the electric vehicle charging station is a large-scale electric vehicle cluster charging terminal, it is necessary to pay attention to the status and controllability of each charging pile. In view of the lack of attention to the actual operation of the electric vehicle charging station in the existing vehicle–network interaction mode, the charging state of the current electric vehicle charging station is fixed. In this paper, deep learning is used to establish a load perception model for electric vehicle charging stations, and K-means clustering is used to optimize the load perception model to realize random load perception and non-intrusive load monitoring stations for electric vehicle charging. The calculation example results show that the proposed method has good performance in the load perception and controllability evaluation of electric vehicle charging stations, and it provides a feasible solution for the practical realization of electric vehicle auxiliary response.
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Dharmawan, I. P., I. N. S. Kumara, and I. N. Budiastra. "PERKEMBANGAN INFRASTRUKTUR PENGISIAN BATERAI KENDARAAN LISTRIK DI INDONESIA." Jurnal SPEKTRUM 8, no. 3 (October 31, 2021): 90. http://dx.doi.org/10.24843/spektrum.2021.v08.i03.p12.
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The development of electric vehicles in Indonesia started after the issuance ofPresidential Decree 55/2019 about battery-based eletric vehicles. The development of electricvehicles must be supported with the charging infrastructure so users do not experienceproblems in charging the vehicles and therefore more people will switch to electric vehicle. Thispaper discusses the current status of charging infrastructure for electric vehicle in Indonesia.Currently, there are several type of vehicle charging facilites consist of 7.000 public electriccharging station or SPLU, 97 public electric vehicle charging station or SPKLU, 9 public electricvehicle battery exchange station or SPBKLU distributed across Sumatra, Java, Bali, NTB,Sulawsi and Kalimantan. In the case of Bali, there are 166 of SPLU, 5 of SPKLU, and there isno SPBKLU yet. The total accumulative energy consumed through the charging stations in Baliis 169.481 kWh. The figure is low due to lack of information about the charging station and thefact that the number of electric vehicles in Bali is still low.
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Jin, Ruijiu, Xiangfeng Zhang, Zhijie Wang, Wengang Sun, Xiaoxin Yang, and Zhong Shi. "Blockchain-Enabled Charging Right Trading Among EV Charging Stations." Energies 12, no. 20 (October 16, 2019): 3922. http://dx.doi.org/10.3390/en12203922.
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Increasing penetration of electric vehicles (EVs) gives rise to the challenges in the secure operation of power systems. The EV charging loads should be distributed among charging stations in a fair and incentive-compatible manner while ensuring that power transmission and transformation facilities are not overloaded. This paper first proposes a charging right (or charging power ration) trading mechanism and model based on blockchain. Considering all kinds of random factors of charging station loads, we use Monte Carlo modeling to determine the charging demand of charging stations in the future. Based on the charging demand of charging stations, a charging station needs to submit the charging demand for a future period. The blockchain first distributes initial charging right in a just manner and ensures the security of facilities. Given that the charging urgency and elasticity differences vary by charging stations, all charging stations then proceed with double auction and peer-to-peer (P2P) transaction of charging right. Bids and offers are cleared via double auctions if bids are higher than offers. The remaining bids and offers are cleared via the P2P market. Then, this paper designs the charging right allocation and trading platform and smart contract based on the Ethernet blockchain to ensure the safety of the distribution network (DN) and the transparency and efficiency of charging right trading. Simulation results based on the Ethereum private blockchain show the fairness and efficiency of the proposed mechanism and the effectiveness of the method and the mechanism.
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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 (May 19, 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 electric vehicle charging station location and volume is established, and the model based on artificial immune algorithm is used to optimize the solution. An empirical analysis was conducted based on a typical regional survey. The research results show that increasing the density of charging stations, lowering the charging price and shortening the charging time can effectively improve user satisfaction. The constructed site and capacity selection optimization solving model can scientifically guide charging station resource allocation under the constraints of the optimal user comprehensive satisfaction target, improve the capacity of scientific planning and resource allocation of regional electric vehicle charging stations, and support the large-scale promotion and application of electric vehicles.
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Elahe, Md Fazla, Md Alamgir Kabir, S. M. Hasan Mahmud, and Riasat Azim. "Factors Impacting Short-Term Load Forecasting of Charging Station to Electric Vehicle." Electronics 12, no. 1 (December 23, 2022): 55. http://dx.doi.org/10.3390/electronics12010055.
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The rapid growth of electric vehicles (EVs) is likely to endanger the current power system. Forecasting the demand for charging stations is one of the critical issues while mitigating challenges caused by the increased penetration of EVs. Uncovering load-affecting features of the charging station can be beneficial for improving forecasting accuracy. Existing studies mostly forecast electricity demand of charging stations based on load profiling. It is difficult for public EV charging stations to obtain features for load profiling. This paper examines the power demand of two workplace charging stations to address the above-mentioned issue. Eight different types of load-affecting features are discussed in this study without compromising user privacy. We found that the workplace EV charging station exhibits opposite characteristics to the public EV charging station for some factors. Later, the features are used to design the forecasting model. The average accuracy improvement with these features is 42.73% in terms of RMSE. Moreover, the experiments found that summer days are more predictable than winter days. Finally, a state-of-the-art interpretable machine learning technique has been used to identify top contributing features. As the study is conducted on a publicly available dataset and analyzes the root cause of demand change, it can be used as baseline for future research.
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Zhao, Yutong, Hong Huang, Xi Chen, Baoqun Zhang, Yiguo Zhang, Yuan Jin, Qian Zhang, Lin Cheng, and Yanxia Chen. "Charging Load Allocation Strategy of EV Charging Station Considering Charging Mode." World Electric Vehicle Journal 10, no. 2 (June 23, 2019): 47. http://dx.doi.org/10.3390/wevj10020047.
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A charging load allocation strategy for Electric Vehicles (EVs) considering charging mode is proposed in this paper in order to solve the challenge and opportunity of large-scale grid-connected charging under the background of booming EV industry in recent years. Based on the peak-to-valley Time-of-Use (TOU) price, this strategy studies the grid load, charging cost and charging station revenue variation of EVs connected to the grid in different charging modes. In addition, this paper proposes an additional charging mechanism for charging stations to encourage EV owners to participate in the peak and valley reduction of the grid through coordinated charging. According to the example analysis, under the same charging demand conditions, the larger EV charging power will have a greater impact on the grid than the conventional charging power. This article collects additional service fees for car owners who are not involved in the coordinated charging. When the response charging ratio is less, the more total service charges are charged, which can compensate for the decline in the sales revenue of the charging station during the valley period. While having good economy, it can also encourage the majority of car owners to participate in the coordinated charging from the perspective of charging cost.
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Li, Wenzao, Lingling Yang, Zhan Wen, Jiali Chen, and Xi Wu. "On the Optimization Strategy of EV Charging Station Localization and Charging Piles Density." Wireless Communications and Mobile Computing 2021 (February 23, 2021): 1–13. http://dx.doi.org/10.1155/2021/6675841.
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The penetration rate of electronic vehicles (EVs) has been increasing rapidly in recent years, and the deployment of EV infrastructure has become an increasingly important topic in some solutions of the Internet of Things (IoT). A reasonable balance needs to be struck between the user experience and the deployment cost of charging stations and the number of charging piles. The deployment of EV’s charging station is a challenging problem due to the uneven distribution and mobility of EV. Fortunately, EVs move with a certain regularity in the urban environment. It makes the deployment strategy design of EV charging stations feasible. Therefore, we proposed a deployment strategy of EV charging station based on particle swarm optimization algorithm to determine the charging station localization and number of charging piles. This strategy is designed based on the nonuniform distribution of EV in a city scene map, at the same time, the distribution of EV at different times, which makes the strategy more reasonable. Extensive simulation results further demonstrated that the proposed strategy can significantly outperform the K-means algorithm in the urban environment.
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Yadnik, Shubham, and Dr Shruti Tiwari. "Renewable Energy based Multimode Electric Vehicle Charging Station: A Review." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 2990–97. http://dx.doi.org/10.22214/ijraset.2022.41951.
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Abstract: The goal of this work is to understand working of renewable energy based multimode EV charging station that should be suited for fast charging of Electric Vehicle and that must be putting the least amount of overload on the Utility-grid. The charging station is operated in such way that it is either powered by solar PV-array system or utility-grid, to improve grid stability during peak load hours. A DC bus connects the PV-array interfaced with DC-to-DC converter and the Utility-grid interfaced with DC to AC bidirectional converter. The efficiency of the utilized control approach is decided by a smooth transition between solar connected mode and grid connected mode. Although charging station infrastructure can be employed in many ways like it can be made only grid connected or only solar power connected but the coordinated operation of solar power system and grid can be efficient and economic option for implementation of EV charging stations on large scale. This renewable energy based multimode EV charging station can prove to be very much useful for reducing dependency on fossil fuel-based vehicles and promoting use of electric vehicles on large scale with very reasonable per unit cost of charging them. Keywords: Photovoltaic array (PV), Renewable energy, Grid connected EV Charging station, Electric Vehicle, Hybrid EV charging station
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Sen, KB, and Rajkumar G. "Solar Powered Charging Station for Electric Vehicle." Journal of Electrical Engineering and Automation 5, no. 2 (June 2023): 238–51. http://dx.doi.org/10.36548/jeea.2023.2.007.
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As the demand for sustainable transportation continues to grow, the integration of renewable energy sources into Electric Vehicle (EV) charging infrastructure has become a vital focus. The concept and benefits of a solar-powered EV charging station proposed in this research, combines solar Photovoltaic (PV) technology with efficient charging infrastructure. The solar-powered EV charging station serves as an innovative solution that harnesses clean and renewable energy from the sun to charge electric vehicles. By leveraging solar PV panels, this charging station reduces reliance on traditional grid electricity, decreases carbon emissions, and promotes sustainable mobility. Furthermore, this study discusses the potential challenges and considerations involved in implementing a solar-powered EV charging station, including site selection, system sizing, grid interconnection, and maintenance requirements. It emphasizes the need for collaboration between renewable energy experts, charging infrastructure providers, and relevant stakeholders to address these challenges and drive the adoption of solar-powered EV charging stations. In conclusion, the abstract presents the solar-powered EV charging station as a sustainable and forward-thinking solution for promoting cleaner transportation. By leveraging solar energy, this charging infrastructure contributes to the reduction of greenhouse gas emissions, fosters energy resilience, and paves the way for a greener future in the realm of electric mobility. It is observed that the proposed system is more efficient than the existing system in terms of fast operation.
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Wang, Zhenpo, Peng Liu, Jia Cui, Yue Xi, and Lei Zhang. "Research on Quantitative Models of Electric Vehicle Charging Stations Based on Principle of Energy Equivalence." Mathematical Problems in Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/959065.
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In order to adapt the matching and planning requirements of charging station in the electric vehicle (EV) marketization application, with related layout theories of the gas stations, a location model of charging stations is established based on electricity consumption along the roads among cities. And a quantitative model of charging stations is presented based on the conversion of oil sales in a certain area. Both are combining the principle based on energy consuming equivalence substitution in process of replacing traditional vehicles with EVs. Defined data are adopted in the example analysis of two numerical case models and analyze the influence on charging station layout and quantity from the factors like the proportion of vehicle types and the EV energy consumption at the same time. The results show that the quantitative model of charging stations is reasonable and feasible. The number of EVs and the energy consumption of EVs bring more significant impact on the number of charging stations than that of vehicle type proportion, which provides a basis for decision making for charging stations construction layout in reality.
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Danial, Muhammad, Fatin Amanina Azis, and Pg Emeroylariffion Abas. "Techno-Economic Analysis and Feasibility Studies of Electric Vehicle Charging Station." World Electric Vehicle Journal 12, no. 4 (December 15, 2021): 264. http://dx.doi.org/10.3390/wevj12040264.
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Recent United Nations high-level dialogue on energy, which had emphasized on energy usage and environmental protection, has renewed commitments by different countries on the adoption of electric vehicle (EVs). This paper aims to analyze the economic feasibility of establishing electrical charging stations, which is an important factor for the wide adoption of EVs, using life cycle cost analysis. Although local data have been used, the method can be easily adopted to analyze economic feasibility at different markets. The findings have revealed that an electrical charging station is only feasible when the acquisition cost is kept to a minimum to return 1.47 times the initial investment in terms of life cycle cost. An acquisition cost of BND 29,725 on the electrical charging station represents the threshold below which an electrical charging station is more attractive. In order to promote these charging stations, the government needs to provide multiple incentives, including a subsidy to reduce the acquisition cost, relaxing control on the electric selling price, taxing the establishment of conventional filling stations, and minimally reducing the profit margin on the selling price of fossil fuel. It has been shown that a 40% initial subsidy on the purchase of electrical charging stations, coupled with a slight subsidy of BND 0.018/kWh on electricity, would make electrical charging stations economically competitive. To reach its target of 60% electrification of the transportation sector, Brunei would need to implement a structure program to establish between 646 and 3300 electrical charging stations by the year 2035, to cater for its expected number of EVs.
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Reddy, Hanumantha, Bhargav B, Sunil S, Santosh Kumar K, and Praveena K. "Solar Off-Grid Electric Vehicle Charging Station." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 3859–62. http://dx.doi.org/10.22214/ijraset.2023.50988.
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Abstract: Nowadays, there is a great development in electric vehicle production and utilization. It has no pollution, high efficiency, low noise, and low maintenance. However, the charging stations, required to charge the electric vehicle batteries, impose high energy demand on the utility grid. One way to overcome the stress on the grid is the utilization of renewable energy sources such as photovoltaic energy. The utilization of standalone charging stations represents good support to the utility grid. Nevertheless, the electrical design of these systems has different techniques and is sometimes complex. This paper introduces a new simple analysis and design of a standalone charging station powered by photovoltaic energy. Simple closed-form design equations are derived, for all the system components. Case-study design calculations are presented for the proposed charging station. Other important features of an off-grid solar EV charging station might include the use of smart charging technology to optimize charging speed and efficiency, as well as the ability to monitor and control the system remotely. Safety features such as overcharge protection and grounding would also be important considerations. We can visualize the expected results using a Cayenne Software, we can also control the street lighting by Internet of Things. The results show that the charging process of the electric vehicle battery is precisely steady for all the PV insolation disturbances. In addition, the charging/discharging of the energy storage battery responds perfectly to store and compensate for PV energy variations.
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Mortimer, Benedict J., Christopher Hecht, Rafael Goldbeck, Dirk Uwe Sauer, and Rik W. De Doncker. "Electric Vehicle Public Charging Infrastructure Planning Using Real-World Charging Data." World Electric Vehicle Journal 13, no. 6 (May 24, 2022): 94. http://dx.doi.org/10.3390/wevj13060094.
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The current increase of electric vehicles in Germany requires an adequately developed charging infrastructure. Large numbers of public and semi-public charging stations are necessary to ensure sufficient coverage. To make the installation worthwhile for the mostly private operators as well as public ones, a sufficient utilization is decisive. An essential factor for the degree of utilization is the placement of a charging station. Therefore, the initial site selection plays a critical role in the planning process. This paper proposes a charging station placement procedure based on real-world data on charging station utilization and places of common interest. In the first step, we correlate utilization rates of existing charging infrastructure with places of common interest such as restaurants, shops, bars and sports facilities. This allows us to estimate the untapped potential of unexploited areas across Germany in a second step. In the last step, we employ the resulting geographical extrapolation to derive two optimized expansion strategies based on the attractiveness of locations for electric vehicle charging.
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Jafari Kaleybar, Hamed, Mostafa Golnargesi, Morris Brenna, and Dario Zaninelli. "Hybrid Energy Storage System Taking Advantage of Electric Vehicle Batteries for Recovering Regenerative Braking Energy in Railway Station." Energies 16, no. 13 (July 2, 2023): 5117. http://dx.doi.org/10.3390/en16135117.
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Nowadays, nations are moving toward the electrification of the transportation section, and the widespread development of EV charging stations and their infrastructures supplied by the grid would strain the power grid and lead to overload issues in the network. To address this challenge, this paper presents a method for utilizing the braking energy of trains in railway stations to charge EVs located in strategic areas like park-and-ride regions close to railway stations improving energy efficiency and preventing grid overload. To validate the feasibility of the proposed system, a metro substation in Milan city is considered as a case study located in outskirts of the city and contains large number of parking space for vehicles. Three different scenarios are evaluated including DC fast charging station, AC low charging station and collaborative hybrid energy storage based AC charging station as EV charging station type. The results are studied for different EV population number, charging rate and the contractual power grid. Meanwhile, the possibility of proposed system in participating as V2G technology and taking advantage of the EV’s batteries to provide ancillary support to accelerating trains is investigated regarding peak shaving objective. The results indicated that the suggested interconnected system operates effectively when a significant quantity of EVs are parked at the station. However, the results revealed that the performance of the proposed system is notably influenced by other factors and a limited number of EVs during the early morning and late evening periods. Overall, this study confirms the feasibility of energy transfer between two types of transportation means in intermodal areas.
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Jang, Moon-Jong, Taehoon Kim, and Eunsung Oh. "Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea." Sustainability 15, no. 10 (May 12, 2023): 7938. http://dx.doi.org/10.3390/su15107938.
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With the widespread use of electric vehicles (EVs), the potential to utilize them as flexible resources has increased. However, the existing vehicle-to-grid (V2G) studies have focused on V2G operation methods. The operational performance is limited by the amount of availability resources, which represents the flexibility. This study proposes a data-driven modeling method to estimate the V2G flexibility. A charging station is a control point connected to a power grid for V2G operation. Therefore, the charging stations’ statuses were analyzed by applying the basic queuing model with a dataset of 1008 chargers (785 AC chargers and 223 DC chargers) from 500 charging stations recorded in Korea. The basic queuing model obtained the long-term average status values of the stations over the entire time period. To estimate the V2G flexibility over time, a charging station status modeling method was proposed within a time interval. In the proposed method, the arrival rate and service time were modified according to the time interval, and the station status was expressed in a propagated form that considered the current and previous time slots. The simulation results showed that the proposed method effectively estimated the actual value within a 10% mean absolute percentage error. Moreover, the determination of V2G flexibility based on the charging station status is discussed herein. According to the results, the charging station status in the next time slot, as well as that in the current time slot, is affected by the V2G. Therefore, to estimate the V2G flexibility, the propagation effect must be considered.
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Shubham, Yadnik, and Tiwari Shruti. "Simulation of hybrid electrical vehicle charging station in multimode operation." i-manager's Journal on Power Systems Engineering 9, no. 4 (2022): 18. http://dx.doi.org/10.26634/jps.9.4.18692.
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The use of electric vehicles is growing very rapidly, and more and more people are switching to electric vehicles as the problem of air pollution has become a concern in most parts of the world. In addition, the spike in fuel prices around the world has prompted people to opt for an alternative vehicle option other than conventional Internal Combustion Engine (ICE) vehicles. But as the number of electric vehicles increases, the need to install charging stations on a very large scale also increases. The main problem with conventional grid-based charging stations is that they increase the load on the main grid and affect the power quality of the local distribution network. This paper discusses the modeling and simulation of a hybrid electric vehicle charging station operating in multi-mode (i.e., grid-connected or Grid Power Connected Mode (GPCM) and solar-powered or Solar Power Connected Mode (SPCM). The Electric Vehicle (EV) charge controller automatically switches between GPCM and SPCM. With this hybrid electric vehicle charging station model, renewable energy can be integrated with the main grid to improve the efficiency and reliability of the electric vehicle charging station, so the Electric Vehicle Charging Station (EVCS) hybrid model can help to expand the electric vehicle charging network on a large scale. The simulation was performed using MATLAB 2016.
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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 (May 17, 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 is used to minimize the combined cost of users and charging stations as the objective. In addition, an improved artificial bee colony algorithm is designed to solve the model. The improved algorithm adds a neighborhood search method and a feasible decoding scheme to the honey bee harvesting and tracking process, thus solving the problems of low search accuracy, poor convergence, and inability to directly calculate the mixed integer model of the original algorithm. Simulation results show that the improved artificial bee colony algorithm can effectively solve the mixed integer model and has higher search accuracy and convergence speed compared with the traditional method. By applying the algorithm to solve the siting model, the location and number of charging stations can be clearly planned, thus improving charging efficiency and reliability.
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Mazurek, Paweł, and Aleksander Chudy. "An Analysis of Electromagnetic Disturbances from an Electric Vehicle Charging Station." Energies 15, no. 1 (December 30, 2021): 244. http://dx.doi.org/10.3390/en15010244.
Full textAbstract:
The electric vehicles (EVs) could potentially have a significant impact on power quality parameters and distribution networks as they are non-linear loads and their charging might result in tremendous power demand. When connected to the utility grid, a large number of EV charging stations from different manufacturers might create significant harmonic current emissions, impact the voltage profile, and eventually affect the power quality. Nevertheless, practical examples of disturbances from charging stations have not been made public. This paper aims to clarify the characteristics of conductive disturbances and levels of current harmonics generated by charging station and their severity on the quality of electric energy. The analysis was based on tests of a prototype station of an EV charging station integrated with a LED street light. The tests concern the determination of current harmonics and the values of conductive electromagnetic disturbances in the 150 kHz–30 MHz range. The test results of the prototype charger with observed exceedances of current harmonics (25th–39th range) and conducted interference exceedances are comprehensively described. After applying filtering circuits to the final version of the station, retesting in an accredited laboratory showed qualitative compliance.
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R, Gowtham, Guganesh P, Ilanchelvan Harikumar V, Ramachandran K, Udhaya Kumar C, and Priyadharshini A. "IoT-Based Smart Booking of Electric Vehicle Charging Station." Journal of ISMAC 5, no. 2 (June 2023): 100–112. http://dx.doi.org/10.36548/jismac.2023.2.002.
Full textAbstract:
The Immense growth in the implementation of electric vehicles (EVs), has established a path in the advancements of charging infrastructure. Interlinking and connecting the charging stations to a common server is essential for future EV adoption, and this can reduce the user's anxiety. The existing charging stations have not implemented charging slot availability and time scheduling management. The objective of this research is to enhance the current electric vehicle (EV) charging infrastructure by gathering and sharing real-time information about the availability of reserve slots at charging stations. This information is made available to users through an interactive application created with Android Studio, allowing them to locate the closest charging station for their EV. The application utilizes the State of Charge of the EV to assign available charging slots. The proposed real-time predictive charging server infrastructure avoids latency, effectively manages time scheduling, and avoids draining electric vehicle batteries. This proposed system uses the real-time traffic database to estimate the minimum distance path to reach the charging station. The system utilizes soil moisture sensors, Potassium, sodium and phosphorus sensors, and amount of water needed for crops. The system is designed to be energy-efficient, cost-effective, and easy to use. It can be remotely controlled and monitored via a mobile application, allowing farmers to have real-time access to their irrigation systems. This system has the potential to improve crop yields, conserve water resources, and reduce labor costs associated with manual irrigation practices.