The Location of Electric Vehicle Charging Stations based on FRLM with Robust Optimization

2019 ◽  
Vol 33 (08) ◽  
pp. 1959027 ◽  
Author(s):  
Jing-min Wang ◽  
Yan Liu ◽  
Yi-fei Yang ◽  
Wei Cai ◽  
Dong-xuan Wang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Robust Optimization ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Site Selection ◽  
Queuing Theory ◽  
Location Model ◽  
Electric Vehicle Charging ◽  
Charging Stations ◽  
Charging Demand

It is very important for the application of artificial intelligence to accurately and quickly help the electric vehicles to find matching charging facilities. The site selection for electric vehicle charging station (EVCS) is a new field of artificial intelligence application, using artificial intelligence to analyze the current complex urban electric vehicle driving path, and then determining the location of charging stations. This paper proposes a novel hybrid model to decide the location of EVCS. First of all, this paper carries out the flow-refueling location model (FRLM) based on path requirement to determine the site selection of EVCS. Secondly, robust optimization algorithm is used to resolve the location model considering the uncertainty of charging demand. Then, queuing theory, which takes the charging load as a constraint in the location model, is integrated into the model. Last, but not the least, a case is conducted to verify the validity of the proposed model when dealing with location problem. As a result of the above analysis, it is effective to apply robust optimization algorithm and to determine the location of EVCSs effectively when charging demand generated on the path is uncertain. At the same time, queuing theory can help to determine the optimal number of EVCSs effectively, and reduce the cost of building EVCSs.

scholarly journals Selecting Locations of Electric Vehicle Charging Stations Based on the Traffic Load Eliminating Method

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1650 ◽  
Author(s):  
Bong-Gi Choi ◽  
Byeong-Chan Oh ◽  
Sungyun Choi ◽  
Sung-Yul Kim
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Traffic Load ◽  
Queueing Model ◽  
Traffic Data ◽  
Electric Vehicle Charging ◽  
Supply Equipment ◽  
Charging Stations ◽  
Ev Charging ◽  
Charging Demand

Establishing electric vehicle supply equipment (EVSE) to keep up with the increasing number of electric vehicles (EVs) is the most realistic and direct means of promoting their spread. Using traffic data collected in one area; we estimated the EV charging demand and selected priority fast chargers; ranging from high to low charging demand. A queueing model was used to calculate the number of fast chargers required in the study area. Comparison of the existing distribution of fast chargers with that suggested by the traffic load eliminating method demonstrated the validity of our traffic-based location approach.

scholarly journals Optimal Siting of Electric Vehicle Charging Stations Using Pythagorean Fuzzy VIKOR Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Feng-Bao Cui ◽  
Xiao-Yue You ◽  
Hua Shi ◽  
Hu-Chen Liu
Keyword(s):  
Decision Making ◽  
Electric Vehicle ◽  
Site Selection ◽  
Multicriteria Decision Making ◽  
Pythagorean Fuzzy Set ◽  
Fuzzy Vikor ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Alternative Sites ◽  
Charging Stations

Site selection for electric vehicle charging stations (EVCSs) is the process of determining the most suitable location among alternatives for the construction of charging facilities for electric vehicles. It can be regarded as a complex multicriteria decision-making (MCDM) problem requiring consideration of multiple conflicting criteria. In the real world, it is often hard or impossible for decision makers to estimate their preferences with exact numerical values. Therefore, Pythagorean fuzzy set theory has been frequently used to handle imprecise data and vague expressions in practical decision-making problems. In this paper, a Pythagorean fuzzy VIKOR (PF-VIKOR) approach is developed for solving the EVCS site selection problems, in which the evaluations of alternatives are given as linguistic terms characterized by Pythagorean fuzzy values (PFVs). Particularly, the generalized Pythagorean fuzzy ordered weighted standardized distance (GPFOWSD) operator is proposed to calculate the utility and regret measures for ranking alternative sites. Finally, a practical example in Shanghai, China, is included to demonstrate the proposed EVCS sitting model, and the advantages are highlighted by comparing the results with other relevant methods.

scholarly journals GIS-BASED OPTIMUM SITE SELECTION FOR SOLAR ELECTRIC VEHICLE CHARGING STATION: ANKARA-ISTANBUL HIGHWAY CASE

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 267-272
Author(s):  
S. Hisoglu ◽  
R. Comert
Keyword(s):  
Electric Vehicle ◽  
Electric Motor ◽  
Site Selection ◽  
Motor Vehicles ◽  
Slope Aspect ◽  
Traffic Density ◽  
Renewable Energy Resources ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

Abstract. Energy sources are divided into renewable and non-renewable sources. It can be seen that non-renewable energy resources are not adequately meeting the increased demands of worldwide technological developments, increasing population, and global consumption. Therefore, the demand for renewable resources is increasing day by day. When it comes to the use of non-renewable carbon-based fossil fuels, one of the first areas that come to mind is undoubtedly the Automotive sector. Today, it is realized that one of the main reasons for the lack of electric motor cars compared to petroleum fuelled cars, is the scarcity of electric vehicle charging stations and the difficulty of their accessibility. In this study; an analysis of solar-powered electric charging stations site selection was carried out for electric vehicles. The Ankara-Istanbul highway, which has a high traffic density, was chosen as the sample route for the study. Within the scope of the study, the areas where stations can be installed on the highway were carried out using the Multi-Criteria Decision Making Method with the help of Geographic Information System. Solar radiation, slope, aspect, land use/land cover, traffic volume and proximity to the road, criteria of the route, and site selection analysis were determined as input data. The maps of the determined criteria were arranged according to the study area and prepared for analysis. The criteria maps obtained were reclassified according to the above-mentioned criteria and scoring system. After the reclassification process, the weighting of each criteria which affect the analysis was determined by the researched literature and an overlapping process was carried out. According to the results map produced as a result of the overlay analysis, the appropriate area has been determined for the electric charging stations working with solar energy. On the defined route within the scope of the study, a proposal has been made for a total of 13 stations, 8 in Ankara, 3 in Bolu, 1 in Kocaeli, and 1 in Istanbul. This study, it is aimed to encourage automobile users to make greater use of electric motor vehicles, which would be a more environmentally friendly and sustainable choice, and ultimately more economical.

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