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.

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 A Cellular Automata Agent-Based Hybrid Simulation Tool to Analyze the Deployment of Electric Vehicle Charging Stations

2021 ◽  
Vol 13 (10) ◽  
pp. 5421
Author(s):  
Amaro García-Suárez ◽  
José-Luis Guisado-Lizar ◽  
Fernando Diaz-del-Rio ◽  
Francisco Jiménez-Morales
Keyword(s):  
Cellular Automata ◽  
Electric Vehicle ◽  
Combustion Engine ◽  
Traffic Density ◽  
Simulation Tool ◽  
Agent Based ◽  
Electric Vehicle Charging ◽  
Model Combining ◽  
Vehicle Charging ◽  
Charging Stations

We present a hybrid model combining cellular automata (CA) and agent-based modeling (ABM) to analyze the deployment of electric vehicle charging stations through microscopic traffic simulations. This model is implemented in a simulation tool called SIMTRAVEL, which allows combining electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) that navigate in a city composed of streets, avenues, intersections, roundabouts, and including charging stations (CSs). Each EV is modeled as an agent that incorporates complex behaviors, such as decisions about the route to destination or CS, when to drive to a CS, or which CS to choose. We studied three different CS arrangements for a synthetic city: a single large central CS, four medium sized distributed CSs or multiple small distributed CSs, with diverse amounts of traffic and proportions of EVs. The simulator output is found to be robust and meaningful and allows one to extract a first useful conclusion: traffic conditions that create bottlenecks around the CSs play a crucial role, leading to a deadlock in the city when the traffic density is above a certain critical level. Our results show that the best disposition is a distributed network, but it is fundamental to introduce smart routing measures to balance the distribution of EVs among CSs.

scholarly journals DESIGNING GIS-BASED SITE SELECTION MODEL FOR URBAN INVESTMENT PLANNING IN SMART CITIES WITH THE CASE OF ELECTRIC VEHICLE CHARGING STATIONS

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 515-522
Author(s):  
S. Sisman ◽  
I. Ergul ◽  
A. C. Aydinoglu
Keyword(s):  
Electric Vehicle ◽  
Site Selection ◽  
Smart City ◽  
Smart Cities ◽  
Selection Model ◽  
Investment Planning ◽  
Electric Vehicle Charging ◽  
Suitability Map ◽  
Vehicle Charging ◽  
Charging Stations

Abstract. It is of great importance that different sectoral investments such as energy, technology, education, logistics, health, industry, transportation, construction, tourism, which will be realized in globalizing and crowded cities, are made in the most suitable city areas. In order to obtain the maximum efficiency from the unit city area for any sectoral investment activity and to develop more planned and liveable cities, many decision parameters in investment management should be handled rationally by integrated a geographical perspective. In this study, designing GIS-based site selection models was examined for effective decision-making in the investment planning process for smart cities. In this context, different sectoral investment applications examining implementation requirements were determined for smart cities. Electric vehicle charging stations (EVCS) site selection application was determined as a case study, to design a GIS-based integrated site selection model for investment planning in smart city concept. Data preparation and analysis models were designed for determining the most suitable EVCSs location. EVSC site selection affecting criteria and criteria weights (by MCDA techniques) were researched in the literature. For this purpose, 15 criteria defined by three main criteria groups, namely Environmental/ Geographical, Economic Criteria, and Urbanity Criteria were determined. Designed models were performed analysing EVCSs suitability map in Pendik district of Istanbul. Normalized raster maps related to 15 criteria and EVCSs suitability map were produced with five suitability degrees for the Pendik district. Also, by designing the models, an integrated and planned investment mechanism can be developed for the impressive and efficient use of urban resources in smart city investments.

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.

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