scholarly journals Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data

2019 ◽  
Vol 11 (3) ◽  
pp. 643 ◽  
Author(s):  
Jianmin Jia ◽  
Chenhui Liu ◽  
Tao Wan
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Travel Demand ◽  
Cellular Signaling ◽  
Sustainable Transportation ◽  
Charging Station ◽  
Step Model ◽  
Pollutants Emission ◽  
Effective Component ◽  
Charging Stations

Electric Vehicles (EVs), by reducing the dependency on fossil fuel and minimizing the traffic-related pollutants emission, are considered as an effective component of a sustainable transportation system. However, the massive penetration of EVs brings a big challenge to the establishment of charging infrastructures. This paper presents the approach to locate charging stations utilizing the reconstructed EVs trajectory derived from the Cellular Signaling Data (CSD). Most previous work focused on the commute trips estimated from the number of jobs and households between traffic analysis zones (TAZs). This paper investigated the large-scale CSD and illustrated the method to generate the 24-hour travel demand for each EV. The complete trip in a day for EV was reconstructed through merging the time sequenced trajectory derived from simulation. This paper proposed a two-step model that grouped the charging demand location into clusters and then identified the charging station site through optimization. The proposed approach was applied to investigate the charging behavior of medium-range EVs with Cellular Signaling Data collected from the China Unicom in Tianjin. The results indicate that over 50% of the charging stations are located within the central urban area. The developed approach could contribute to the planning of future charging stations.

scholarly journals A smart management system of electric vehicles charging plans on the highway charging stations

2021 ◽  
Vol 23 (2) ◽  
pp. 752
Author(s):  
Ibrahim El-Fedany ◽  
Driss Kiouach ◽  
Rachid Alaoui
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Long Distance ◽  
Smart Transportation ◽  
Charging Station ◽  
Charging Time ◽  
Trip Time ◽  
Automatic Mechanism ◽  
Charging Stations

Electric vehicles (EVs) are seen as one of the principal pillars of smart transportation to relieve the airborne pollution induced by fossil CO2 emissions. However, the battery limit, especially where the journey is with a long-distance road remains the most formidable obstacle to the large-scale use of EVs. To overcome the issue of prolonged waiting charging time due to the large number of EVs may have a charging plan at the same charging station (CS) along the highway, we propose a communication system to manage the EVs charging demands. The architecture system contains a smart scheduling algorithm to minimize trip time including waiting time, previous reservations and energyare needed to reach the destination. Moreover, an automatic mechanism for updating reservation is integrated to adjust the EVs charging plans. The results of the evaluation under the Moroccan highway scenario connecting Rabat and Agadir show the effectiveness of our proposal system.<br /><div> </div>

scholarly journals Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles

2020 ◽  
Vol 12 (18) ◽  
pp. 7343
Author(s):  
Junpeng Cai ◽  
Dewang Chen ◽  
Shixiong Jiang ◽  
Weijing Pan
Keyword(s):  
Electric Vehicles ◽  
Travel Demand ◽  
Smart Cities ◽  
Travel Distance ◽  
Dijkstra Algorithm ◽  
Shortest Path Algorithm ◽  
Promising Technique ◽  
Charging Station ◽  
Proposed Model ◽  
Charging Stations

With the increasing popularization and competition of electric vehicles (EVs), EV users often have anxiety on their trip to find better charging stations with less travel distance. An intelligent charging guidance strategy and two algorithms were proposed to alleviate this problem. First, based on the next destination of EV users’ trip, the strategy established a dynamic-area model to match charging stations with users’ travel demand intelligently. In the dynamic area, the Dijkstra algorithm is used to find the charging station with the shortest trip. Then, the area extension algorithm and the charging station attribution algorithm were developed to improve the robustness of the dynamic area. The two algorithms can automatically adjust the area size according to the number of charging stations in the dynamic area to reduce the number of nodes traversed by the Dijkstra algorithm. Finally, simulation examples were used to verify the effectiveness of the proposed model and algorithms. The results showed that the proposed intelligent charging guidance strategy can meet the travel demand of users. It is a promising technique in smart cities to find better travel trips with less travel distance and less computed time.

scholarly journals Self-Sustainable off grid Electric Vehicle (EV) Charging Station with Integration of Renewable Sources

2020 ◽  
Vol 9 (3) ◽  
pp. 2669-2674
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Large Scale ◽  
Transport Systems ◽  
Diesel Generator ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Power Generation Technology ◽  
Charging Stations ◽  
Ev Charging

Electric Vehicles (EV) are the world’s future transport systems. With the rise in pollutions and its effects on the environment, there has been a large scale movetowards electrical vehicles. But the plug point availability for charging is the serious problem faced by the mostof Electric Vehicle consumers. Therefore, there is a definite need to move from the GRID based/connected charging stations to standalone off-grid stations for charging the Electric Vehicles. The objective of this paper is to arrive at the best configuration or mix of the renewable resources and energy storage systems along with conventional Diesel Generator set which together works in offgrid for Electric Vehicle charging. As aconclusion, by utilizing self-sustainable off-grid power generation technology, the availability of EV charging stations in remote localities at affordable price can be made and mainly it reduces burden on the existing electrical infrastructure.

scholarly journals How to Make the Charging Simple, Convenient and Efficient

2020 ◽  
Vol 19 (1) ◽  
pp. 76-84
Author(s):  
W. Cheng ◽  
Y. Wang
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Big Data Analysis ◽  
End Users ◽  
Charging Station ◽  
Power Company ◽  
The World ◽  
Point Operator ◽  
Important People ◽  
Charging Stations

With the large-scale application of electric vehicles (EV) in the world and also in China, the contradiction between the EV and charging stations has become more and more prominent. People always cannot easily find the charging stations or when they find them finally found they do not work. To connect the vehicle, charging station/pile and end-users for making the charging simple, convenient, efficient and visible is becoming very important. People need a platform to tell them where, when and how to charge for their EV. Matrix Mobility is focusing on realizing this comprehensive charging solution together with OEM, charging point operator (CPO), electric power company and parking lots by using big data analysis. Matrix Mobility installs the charging solution into the car unit before cars go off production line and meanwhile integrates the same function into OEM’s own APP with opening API to help end-users increase their charging experience.

scholarly journals Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation

2021 ◽  
Vol 13 (11) ◽  
pp. 6163
Author(s):  
Yongyi Huang ◽  
Atsushi Yona ◽  
Hiroshi Takahashi ◽  
Ashraf Mohamed Hemeida ◽  
Paras Mandal ◽  
...  
Keyword(s):  
Power Generation ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
System Optimization ◽  
Mixed Integer ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Photovoltaic Power ◽  
Vehicle Charging ◽  
Charging Stations

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.

scholarly journals Distribution Network Congestion Dispatch Considering Time-Spatial Diversion of Electric Vehicles Charging

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2820 ◽  
Author(s):  
Hui Sun ◽  
Peng Yuan ◽  
Zhuoning Sun ◽  
Shubo Hu ◽  
Feixiang Peng ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution Network ◽  
Network Congestion ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Large Numbers ◽  
Pricing Scheme ◽  
Multiple Charging ◽  
Charging Stations

With the popularization of electric vehicles, free charging behaviors of electric vehicle owners can lead to uncertainty about charging in both time and space. A time-spatial dispatching strategy for the distribution network guided by electric vehicle charging fees is proposed in this paper, which aims to solve the network congestion problem caused by the unrestrained and free charging behaviors of large numbers of electric vehicles. In this strategy, congestion severity of different lines is analyzed and the relationship between the congested lines and the charging stations is clarified. A price elastic matrix is introduced to reflect the degree of owners’ response to the charging prices. A pricing scheme for optimal real-time charging fees for multiple charging stations is designed according to the congestion severity of the lines and the charging power of the related charging stations. Charging price at different charging station at different time is different, it can influence the charging behaviors of vehicle owners. The simulation results confirmed that the proposed congestion dispatching strategy considers the earnings of the operators, charging cost to the owners and the satisfaction of the owners. Moreover, the strategy can influence owners to make judicious charging plans that help to solve congestion problems in the network and improve the safety and economy of the power grid.

scholarly journals Locating Multiple Size and Multiple Type of Charging Station for Battery Electricity Vehicles

2018 ◽  
Vol 10 (9) ◽  
pp. 3267 ◽  
Author(s):  
Shaohua Cui ◽  
Hui Zhao ◽  
Huijie Wen ◽  
Cuiping Zhang
Keyword(s):  
Travel Time ◽  
Electric Vehicles ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Range Limit ◽  
Mixed Integer Linear Program ◽  
Charging Station ◽  
Different Types ◽  
Initial Charge ◽  
Charging Stations

As environmental and energy issues have attracted more and more attention from the public, research on electric vehicles has become extensive and in-depth. As driving range limit is one of the key factors restricting the development of electric vehicles, the energy supply of electric vehicles mainly relies on the building of charging stations, battery swapping stations, and wireless charging lanes. Actually, the latter two kinds of infrastructure are seldom employed due to their immature technology, relatively large construction costs, and difficulty in standardization. Currently, charging stations are widely used since, in the real world, there are different types of charging station with various levels which could be suitable for the needs of network users. In the past, the study of the location charging stations for battery electric vehicles did not take the different sizes and different types into consideration. In fact, it is of great significance to set charging stations with multiple sizes and multiple types to meet the needs of network users. In the paper, we define the model as a location problem in a capacitated network with an agent technique using multiple sizes and multiple types and formulate the model as a 0–1 mixed integer linear program (MILP) to minimize the total trip travel time of all agents. Finally, we demonstrate the model through numerical examples on two networks and make sensitivity analyses on total budget, initial quantity, and the anxious range of agents accordingly. The results show that as the initial charge increases or the budget increases, travel time for all agents can be reduced; a reduction in range anxiety can increase travel time for all agents.

scholarly journals Operating Charging Infrastructure in China to Achieve Sustainable Transportation: The Choice between Company-Owned and Franchised Structures

2019 ◽  
Vol 11 (6) ◽  
pp. 1549 ◽  
Author(s):  
Lin Ma ◽  
Yuefan Zhai ◽  
Tian Wu
Keyword(s):  
Electric Vehicles ◽  
Rapid Development ◽  
Sustainable Transportation ◽  
Sustainable Infrastructure ◽  
Charging Infrastructure ◽  
Initial Stage ◽  
Charging Stations ◽  
Operation Cost ◽  
Optimal Quality

The rapid development of electric vehicles (EVs) is conducive to clean transportation, which is an important aspect of sustainable infrastructure. However, the introduction of EVs is constrained by the lagging development of EV chargers. To optimally promote the development of charging stations, we analyzed the differences in the optimal quality and quantity of EV chargers between company-owned and franchised enterprises by constructing a theoretical model, and the changes in the quality and quantity of EV chargers in different market environments are discussed. We found that the total number of franchised charging stations was larger in general, but that the quality of the franchised charging stations was worse compared with the company-owned stations. The supervision cost, operation cost, and the investment return affect the quality and quantity of EV chargers. Although franchised structures are more conducive in the initial stage to increasing the number of charging stations to meet the needs of EVs, company-owned structures perform better and will be needed to improve the quality of the EV chargers as the market becomes more saturated, necessitating a higher quality of EV chargers.

scholarly journals Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4682 ◽  
Author(s):  
Grzegorz Sierpiński ◽  
Marcin Staniek ◽  
Marcin Jacek Kłos
Keyword(s):  
Decision Making ◽  
Electric Vehicles ◽  
Urban Areas ◽  
Minimum Energy ◽  
Initial State ◽  
Local Authorities ◽  
Additional Energy ◽  
Charging Station ◽  
Charging Stations ◽  
Decision Making Support

Development of electromobility in urban areas requires an appropriate level of vehicle charging infrastructure. Numerous methods for siting of charging stations have been developed to date, and they appear to be delivering diverse outcomes for the same area, which is why local authorities face the problem of choosing the right station layout. The solution proposed in this article is to use a travel planner to evaluate the distribution of charging stations over the area of a metropolis. The decision making support is achieved by determining optimal travel routes for electric vehicles according to their initial state of charge for the three selected station siting methods. The evaluation focused on the following three aspects: (1) number of travels that cannot be made (due to the lack of a charging station at a certain distance around the start point), (2) extension of the travel caused by the need to recharge the vehicle on-route, and (3) additional energy consumption by electric vehicles required to reach the charging station (necessity of departing from the optimal route). An analysis of the results has made it possible to determine a solution which is superior to others. For the case study analysed in the paper, i.e., the territory of the Metropolis of Upper Silesia and Dabrową Basin (Górnośląsko-Zagłębiowska Metropolia, GZM), the distribution of charging stations established in line with method I has returned the best results. What the method in question also makes possible is to indicate a safe minimum energy reserve to complete the travel by eliminating situations of unexpected vehicle immobilisation due to on-route energy depletion and by minimising the phenomenon referred to as range anxiety.

Study on the Harmonic Impact of Large Scale Electric Vehicles to Grid

2013 ◽  
Vol 443 ◽  
pp. 273-278 ◽  
Author(s):  
Ceng Ceng Hao ◽  
Yue Jin Tang ◽  
Jing Shi
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Large Scale ◽  
Flow Distribution ◽  
Electric Grid ◽  
Nonlinear Loads ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations ◽  
Harmonic Problem

Large scale electric vehicles integration into power grid, as nonlinear loads, will pose inevitable impacts on the operation of power system, one of which the harmonic problem will affect the power quality greatly. Firstly, the article analyzes the characteristics of harmonic caused by electric vehicle charging. And then, the harmonic flow distribution is analyzed based on the IEEE standard node systems. During transient analyses, the electric vehicle charging stations connected to electric grid are represented as harmonic sources. Results show that structure and voltage grade of electric grid, capacity and access points of electric vehicle charging load will have different effects on harmonic problem. At last, a few conclusions are given for connecting electric vehicles to electric grid.

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