scholarly journals Location of Charging Stations in Electric Car Sharing Systems

2020 ◽  
Vol 54 (5) ◽  
pp. 1408-1438
Author(s):  
Georg Brandstätter ◽  
Markus Leitner ◽  
Ivana Ljubić
Keyword(s):  
Electric Vehicles ◽  
Optimization Problem ◽  
Computational Study ◽  
Exact Algorithm ◽  
Grid Graph ◽  
Car Sharing ◽  
Sequential Approach ◽  
Electric Car ◽  
Benchmark Instances ◽  
Charging Stations

Electric vehicles are prime candidates for use within urban car sharing systems, both from economic and environmental perspectives. However, their relatively short range necessitates frequent and rather time-consuming recharging throughout the day. Thus, charging stations must be built throughout the system’s operational area where cars can be charged between uses. In this work, we introduce and study an optimization problem that models the task of finding optimal locations and sizes for charging stations, using the number of expected trips that can be accepted (or their resulting revenue) as a gauge of quality. Integer linear programming formulations and construction heuristics are introduced, and the resulting algorithms are tested on grid-graph-based instances, as well as on real-world instances from Vienna. The results of our computational study show that the best-performing exact algorithm solves most of the benchmark instances to optimality and usually provides small optimality gaps for the remaining ones, whereas our heuristics provide high-quality solutions very quickly. Our algorithms also provide better solutions than a sequential approach that considers strategic and operational decisions separately. A cross-validation study analyzes the algorithms’ performance in cases where demand is uncertain and shows the advantage of combining individual solutions into a single consensus solution, and a simulation study investigates their behavior in car sharing systems that provide their customers with more flexibility regarding vehicle selection.

scholarly journals Modelling and Performance Analysis of Electric Car-Sharing Systems Using Petri Nets

2020 ◽  
Vol 170 ◽  
pp. 03001 ◽  
Author(s):  
A. Hamroun ◽  
K. Labadi ◽  
M. Lazri
Keyword(s):  
Petri Nets ◽  
Simulation Analysis ◽  
Discrete Event ◽  
Stochastic Petri Nets ◽  
Car Sharing ◽  
Event Simulation ◽  
Electric Car ◽  
Bike Sharing ◽  
And Performance ◽  
Charging Stations

Car sharing systems emerged as a new answer to mobility challenges in smart and sustainable cities. Despite their apparent success, design and exploitation of such systems raise crucial strategic and operational challenges. To help planners and decision makers, simulation, analysis and optimization models are unavoidable. Based on the formal modelling and analysis power of stochastic Petri nets, this paper proposes a discrete event simulation model for electric car sharing systems for performance and analysis purposes, taking into account their complex dynamic behaviour, organization and parameters including capacities of the stations, battery and energy availability, locations of charging stations and also their car maintenance activities, not negligible compared to the case of bike-sharing systems.

Efficient Solution of Maximum-Entropy Sampling Problems

2020 ◽  
Vol 68 (6) ◽  
pp. 1826-1835
Author(s):  
Kurt M. Anstreicher
Keyword(s):  
Maximum Entropy ◽  
Efficient Solution ◽  
Optimization Problem ◽  
Exact Algorithm ◽  
Discrete Optimization Problem ◽  
Monitoring Networks ◽  
Benchmark Instances ◽  
Sampling Problem ◽  
Sampling Problems ◽  
First Time

Maximum-entropy sampling is a difficult nonlinear discrete optimization problem that arises in spatial statistics, for example, in the design of weather-monitoring networks. An exact algorithm for maximum-entropy sampling was first described in 1995, and subsequent papers have devised a variety of methods that obtain bounds and, in some cases, exact solutions. In “An Efficient Algorithm for Maximum-Entropy Sampling,” Anstreicher describes a new bound for the maximum-entropy sampling problem that is superior to all previously known bounds and is also efficiently computable. A branch-and-bound algorithm that incorporates the new bound solves challenging benchmark instances to optimality for the first time.

scholarly journals An Evaluation Framework for the Planning of Electric Car-Sharing Systems: A Combination Model of AHP-CBA-VD

2019 ◽  
Vol 11 (20) ◽  
pp. 5627 ◽  
Author(s):  
Yixi Xue ◽  
Yi Zhang ◽  
Yi Chen
Keyword(s):  
Electric Vehicles ◽  
Planning Process ◽  
Cost Benefit Analysis ◽  
Evaluation Criteria ◽  
Relative Weight ◽  
Cost Benefit ◽  
Evaluation Framework ◽  
Car Sharing ◽  
Electric Car ◽  
Routine Inspection

The combination of car-sharing and electric vehicles can increase the acceptance of electric vehicles and facilitate car-sharing to be a more sustainable means of transport. However, this also poses more challenges for the good planning of electric car-sharing systems. To assist car-sharing companies in improving the planning decisions, this paper developed an evaluation framework from a comprehensive view. In the first step, four evaluation criteria were identified according to the planning process: construction of stations; routine inspection; vehicle usability and relocation management; and the maintenance and replacement of stations. Then, a combinatorial method based on analytic hierarchy process (AHP), cost-benefit analysis (CBA), and Voronoi diagram (VD) is developed to determine the relative weight of the four criteria and evaluate the alternative. Finally, the evaluation framework was applied in a realistic case of EVCARD, which is the most influential electric car-sharing company in China. The performance of two different operational districts of EVCARD—Jingan and Changning—were compared. The results showed that vehicle usability and relocation management is the greatest criterion influencing the planning performance of the electric car-sharing system in China, and that routine inspection is a negligible but important factor. According to the relative scores, Jiagan District performed better than Changning district.

scholarly journals MATHEMATICAL MODELS OF PROBLEMS OF OPTIMAL PLACEMENT OF ELECTRIC CAR CHARGING STATIONS AND DETERMINATION OF THEIR SERVICE AREAS

2021 ◽  
pp. 253-256
Author(s):  
Andrii Maliienko
Keyword(s):  
Mathematical Models ◽  
Simultaneous Determination ◽  
Electric Vehicles ◽  
Optimal Placement ◽  
Electric Transport ◽  
Electric Car ◽  
Service Areas ◽  
Multiple Coverage ◽  
Charging Stations

Modern requirements of transport communication require the use of more environmentally friendly transport, and electric transport requires a more thorough analysis of the locations of its service points, including charging stations for electric vehicles. In this paper, it is proposed to use the theory and methods of multiple coverage of sets for modeling and solving problems of optimal placement of charging stations of electric vehicles with simultaneous determination of their service areas, taking into account the possibility of overlap.

Electric Car-Sharing as a Solution Supporting the Development of Electromobility and an Element of the Travel Chain

2020 ◽  
pp. 211-229
Author(s):  
Grzegorz Sierpiński ◽  
Katarzyna Turoń
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Carbon Footprint ◽  
Environmentally Friendly ◽  
Car Sharing ◽  
Electric Car ◽  
The City ◽  
Positive Effect

The recently observed increase in the number of car-sharing operators using a fleet of electric vehicles created an opportunity to expand existing ecological travel chains. Electromobility is one of travelling options that reduces the transport carbon footprint. The goal of the chapter is to draw attention to the need of using car-sharing to promote environmentally friendly behavior and overcome concerns related to using an electric vehicle. The work presents the development of electric car-sharing in Europe and indicates challenges for further expansion of electromobility. By adding electric-car-sharing to the travel chain, the perception of ecological travelling significantly changes, since it combines various advantages for the user (e.g., comfort of travelling and individual trip) and a positive effect of such a choice on the environment and the city.

scholarly journals Magyarország térinformatikai alapú gyorsforgalmi átjárhatósági vizsgálata az elektromobilitás szempontjából– helyzetkép és fejlesztési lehetőségek

2021 ◽  
Vol 145 (1) ◽  
pp. 50-66
Keyword(s):  
Electric Vehicles ◽  
Long Distance ◽  
Comparative Analyses ◽  
Inner Cities ◽  
Strategic Objective ◽  
Long Distance Transport ◽  
Electric Car ◽  
Charging Stations ◽  
Distance Transport

In the context of this research, two aspects, namely coverage and linear availability, have been examined for the possibility of quick charging of battery-powered electric vehicles in Hungary, focusing on national connectivity. It has been shown that the density of quick chargers is uneven; that is, they are present in the inner cities at a higher rate than along motorways for long-distance transport. The study carried out comparative analyses based on two previously published concepts (E.ON–MOL and BME KKT) and a dedicated methodology (ELTE KTF) using the potential charging sites outlined therein. Modelling has shown that the electric car charging possibilities available along the highways are limited. The investigation suggests that the strategic objective should not be to establish a charging network for national connectivity, since only 5%of the charging stations are currently located in the immediate vicinity of motorways and only half of which are quick chargers.

scholarly journals Toward a Unified Model Approach for Evaluating Different Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6120
Author(s):  
Wael Alosaimi ◽  
Md Tarique Jamal Ansari ◽  
Abdullah Alharbi ◽  
Hashem Alyami ◽  
Saquib Ali ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Fuzzy Ahp ◽  
Unified Model ◽  
Combustion Engines ◽  
The Past ◽  
Electric Car ◽  
Different Types ◽  
Charging Stations ◽  
Improved Technology ◽  
Model Approach

Considering rising pollution as well as fuel expenses, it has now become critical to transition to a sustainable method of transportation. As a result, automakers have begun to spend on research and development in the electric vehicle (EV) industry. The amount of EVs has expanded rapidly in recent years. This is owing to new improved technology, particularly in electric motor engineering, as well as government initiatives to limit the level of environmental impact produced by combustion engines. Because EVs are powered by electricity, implementing their charging stations presents certain complications. In this paper, we have discussed the different types of EVs, such as BEVs, FCEVs, HEVs, PHEVs, and REHEVs. Even though the capacity of many of these electric car models has been substantially enhanced within the past few years, some challenges remain as a selection barrier for several customers. Considering these challenges, we have also implemented a fuzzy AHP-TOPSIS-based unified model to evaluate the different types of EVs. The study’s technical importance is the identification of various evaluation factors, implementation of a unified model for measuring performance, and computation using the fuzzy MCDM technique. The outcomes of the unified model approach also were validated. We concluded that FCEVs are excellent for long journeys, and have the resources to cause minimal disruption.

Optimal Planning of Electric Vehicle Charging Stations Location Based on Hybrid Particle Swarm Optimization

2013 ◽  
Vol 724-725 ◽  
pp. 1355-1360 ◽  
Author(s):  
Zhe Ci Tang ◽  
Chun Lin Guo ◽  
Peng Xin Hou ◽  
Yu Bo Fan ◽  
Dong Ming Jia
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicles ◽  
Particle Swarm ◽  
Operating Costs ◽  
Swarm Optimization ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Electric Car ◽  
Hybrid Particle Swarm Optimization ◽  
Charging Stations

In order to determine the layout of electric car charging stations, a model for optimizing charging stations location is developed after charging-demand districts are divided, the number of electric vehicles and the center of each charging district are ready. This model takes the minimization of electric vehicles charging stations total cost which includes initial fixed investment costs, operating costs and charging costs as the objective function, some related constraints which include service radius, capacity of charging station etc. are considered. Particle swarm optimization based on hybridization is proposed to solve this problem. The example verifies feasibility of this method.

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