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 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.

Layout evaluation for electric vehicle charging pile based on charging frequency

2021 ◽  
pp. 1-13
Author(s):  
Xiangke Cui ◽  
Zhenji Zhang ◽  
Fang Liu ◽  
Jingya Liu
Keyword(s):  
Electric Vehicles ◽  
Factors Affecting ◽  
Charging Station ◽  
Passenger Demand ◽  
Basic Model ◽  
Electric Vehicle Charging ◽  
Total Vehicle ◽  
Improved Model ◽  
Charging Stations ◽  
Station Location

This study aims to solve the problem of locating charging stations for public electric vehicles. We take into consideration the factors affecting charging station locations including mileage, electric vehicles distribution, and passenger distribution. A Non-deterministic Polynomial model aiming to minimize the total vehicle service distance is developed. We use an agent-based model to simulate the optimized charging station location based on Anylogic. Through a case study of Beijing, we test the model in five situations. The results of one situation show that the existing layout of the charging stations is unreasonable when charging frequency is sharply variant (basic model); this paper optimizes the existing location by improving the constraint for the smallest number of charging stations (improved model); compared with the basic model, the improved model has a shorter response time to passenger demand, shorter service time for passengers but more mileage for electric vehicles.

scholarly journals Two - Echelon Vehicle Routing Problem with Recharge Stations

2019 ◽  
Vol 20 (4) ◽  
pp. 305-317
Author(s):  
Anita Agárdi ◽  
László Kovács ◽  
Tamás Bányai
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicles ◽  
Vehicle Routing Problem ◽  
Manufacturing Systems ◽  
Route Planning ◽  
Planning Problem ◽  
Test Results ◽  
Routing Problem ◽  
Efficient Operation ◽  
Wide Range

Abstract The efficient operation of logistic processes requires a wide range of design tasks to ensure efficient, flexible and reliable operation of connected production and service processes. Autonomous electric vehicles support the flexible in-plant supply of cyber-physical manufacturing systems. Within the frame of this article, the extension of the Two-Echelon Vehicle Routing Problem with recharge stations is analyzed. The objective function of the optimization problem is the minimization of operation costs. The extension of 2E-VRP means that the second level vehicles (electric vehicles, must be recharged) come from one recharge station, then pick up the products from the satellite, visit the customers and return to the recharge station from where it started. We solved the route planning problem with the application of construction heuristics and improvement heuristics. The test results indicate that the combination of this approach provides a superior efficiency.

scholarly journals Electric Vehicle Routing Problem in Urban Logistics

2021 ◽  
Vol 6 (4) ◽  
pp. 61
Author(s):  
Yiwei Lu
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Vehicle Routing Problem ◽  
Real Life ◽  
Routing Problem ◽  
Electric Vehicle Charging ◽  
New Research ◽  
Charging Stations ◽  
The Impact

<p><span lang="EN-US">Due to the impact of global warming, diesel locomotives that use fossil energy as fuel are gradually being replaced by electric vehicles. At present, many countries at home and abroad are actively promoting the development of the electric vehicle industry in response to the call of the Paris Agreement. However, electric vehicles have a maximum mileage limit, so the reasonable layout of electric vehicle charging stations is also a problem to be solved today. In this article, the author analyzes the research background of the electric vehicle routing problem. After introducing several new research directions in the current electric vehicle routing problem, we propose an optimization algorithm for solving those types of problem. It brings certain theoretical significance for future generations to solve the problem of electric vehicle routing in real life.</span></p>

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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