scholarly journals Route Planning for a Fleet of Electric Vehicles with Waiting Times at Charging Stations

2019 ◽  
pp. 66-82 ◽  
Author(s):  
Baoxiang Li ◽  
Shashi Shekhar Jha ◽  
Hoong Chuin Lau
Keyword(s):  
Electric Vehicles ◽  
Waiting Times ◽  
Route Planning ◽  
Charging Stations

scholarly journals Routing of Electric Vehicles With Intermediary Charging Stations: A Reinforcement Learning Approach

2021 ◽  
Vol 4 ◽  
Author(s):  
Marina Dorokhova ◽  
Christophe Ballif ◽  
Nicolas Wyrsch
Keyword(s):  
Reinforcement Learning ◽  
Electric Vehicles ◽  
Mathematical Formulation ◽  
Route Planning ◽  
Learning Approach ◽  
Training Procedure ◽  
Routing Problem ◽  
Policy Model ◽  
Model Free ◽  
Charging Stations

In the past few years, the importance of electric mobility has increased in response to growing concerns about climate change. However, limited cruising range and sparse charging infrastructure could restrain a massive deployment of electric vehicles (EVs). To mitigate the problem, the need for optimal route planning algorithms emerged. In this paper, we propose a mathematical formulation of the EV-specific routing problem in a graph-theoretical context, which incorporates the ability of EVs to recuperate energy. Furthermore, we consider a possibility to recharge on the way using intermediary charging stations. As a possible solution method, we present an off-policy model-free reinforcement learning approach that aims to generate energy feasible paths for EV from source to target. The algorithm was implemented and tested on a case study of a road network in Switzerland. The training procedure requires low computing and memory demands and is suitable for online applications. The results achieved demonstrate the algorithm’s capability to take recharging decisions and produce desired energy feasible paths.

scholarly journals Effective Permutation Encoding for Evolutionary Optimization of the Electric Vehicle Routing Problem

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6651
Author(s):  
Remigiusz Iwańkowicz
Keyword(s):  
Electric Vehicles ◽  
Method Development ◽  
Route Planning ◽  
Routing Problem ◽  
Moving Vehicle ◽  
Factors Affecting ◽  
Multiple Vehicles ◽  
Rapid Generation ◽  
Charging Stations ◽  
Computation Speed

This paper addresses the problem of route planning for a fleet of electric vehicles departing from a depot and supplying customers with certain goods. This paper aims to present a permutation-based method of vehicle route coding adapted to the specificity of electric drive. The developed method integrated with an evolutionary algorithm allows for rapid generation of routes for multiple vehicles taking into account the necessity of supplying energy in available charging stations. The minimization of the route distance travelled by all vehicles was taken as a criterion. The performed testing indicated satisfactory computation speed. A real region with four charging stations and 33 customers was analysed. Different scenarios of demand were analysed, and factors affecting the results of the proposed calculation method were indicated. The limitations of the method were pointed out, mainly caused by assumptions that simplify the problem. In the future, it is planned for research and method development to include the lapse of time and for the set of factors influencing energy consumption by a moving vehicle to be extended.

scholarly journals Use of electric vehicles in carsharing to serve the sports events

2020 ◽  
Vol 208 ◽  
pp. 05004
Author(s):  
Arkadii Simdiankin ◽  
Eugeny Zhavoronkov
Keyword(s):  
Electric Vehicles ◽  
Waiting Times ◽  
Subsequent Development ◽  
The European Union ◽  
Environmental Standards ◽  
Significant Progress ◽  
Sports Events ◽  
Battery Capacity ◽  
Independent Direction ◽  
Charging Stations

Carsharing was appeared at the beginning of the last century with the idea of offering cars for rent. The subsequent development of rental allowed carsharing to take shape as an independent direction in 1971 and in 1991 the European car sharing Association was established. Further computerization made this service more accessible. However, in 1992 the European Union introduced the Euro-1 environmental standard. Further tightening of environmental standards has forced firms to take a fresh look at the provision of carsharing services. As a result, owners were turned to cars with hybrid, hydrogen and electric motors. Due to significant progress in increasing battery capacity the electric vehicles are the most promising for this field of activity. However, the issues of placing charging stations in places where electric vehicles are used intensively in order to provide quick access and reduce waiting times in the queue are still not fully worked out.

scholarly journals A Comparative Study of En Route Refuelling Behaviours of Conventional and Electric Vehicles in Beijing, China

2019 ◽  
Vol 11 (14) ◽  
pp. 3869 ◽  
Author(s):  
Chengxiang Zhuge ◽  
Chunfu Shao ◽  
Xia Li
Keyword(s):  
Comparative Study ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Waiting Times ◽  
Level Of Education ◽  
Electric Driving ◽  
The Difference ◽  
Charging Stations ◽  
Beijing China

A comparative study is carried out to investigate the differences among conventional vehicles (CVs), battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) in the maximum acceptable time of diverting to a refuelling station, maximum acceptable time of queueing at a refuelling station, refuelling modes and desirable electric driving ranges, using Beijing, China, as a case study. Here, several multinomial logit (MNL) models are developed to relate the diverting and waiting times to individual attributes. The results suggest that, (1) the diverting time roughly follows a normal distribution for both CVs and electric vehicles (EVs), but the difference between them is slight; (2) EVs tend to bear longer waiting time above 10 min; (3) the MNL models indicate that income and the level of education tend to be more statistically significant to both the diverting and waiting times; (4) the most preferred driving ranges obtained for BEVs and PHEVs are both around 50 km, indicating that EV drivers may just prefer to charge for a specific time ranging from 8 to 10 min. Finally, ways to apply the empirical findings in planning refuelling and charging stations are discussed with specific examples.

Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohamad Nassereddine
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Power Network ◽  
Network Stability ◽  
Fast Charging ◽  
Electrical Loads ◽  
Charging Stations

AbstractRenewable energy sources are widely installed across countries. In recent years, the capacity of the installed renewable network supports large percentage of the required electrical loads. The relying on renewable energy sources to support the required electrical loads could have a catastrophic impact on the network stability under sudden change in weather conditions. Also, the recent deployment of fast charging stations for electric vehicles adds additional load burden on the electrical work. The fast charging stations require large amount of power for short period. This major increase in power load with the presence of renewable energy generation, increases the risk of power failure/outage due to overload scenarios. To mitigate the issue, the paper introduces the machine learning roles to ensure network stability and reliability always maintained. The paper contains valuable information on the data collection devises within the power network, how these data can be used to ensure system stability. The paper introduces the architect for the machine learning algorithm to monitor and manage the installed renewable energy sources and fast charging stations for optimum power grid network stability. Case study is included.

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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