scholarly journals The impact of quick charging stations on the route planning of Electric Vehicles

2017 ◽  
Author(s):  
Bulent Catay ◽  
Merve Keskin
Keyword(s):  
Electric Vehicles ◽  
Route Planning ◽  
Charging Stations ◽  
The Impact

scholarly journals Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Xiaomin Xu ◽  
Dongxiao Niu ◽  
Yan Li ◽  
Lijie Sun
Keyword(s):  
Electric Vehicles ◽  
Optimization Problems ◽  
Power Grid ◽  
Economic Benefits ◽  
Pricing Strategy ◽  
Optimal Pricing ◽  
Electricity Pricing ◽  
Optimal Pricing Strategy ◽  
Charging Stations ◽  
The Impact

Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.

scholarly journals Joint Optimal Policy for Subsidy on Electric Vehicles and Infrastructure Construction in Highway Network

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2479 ◽  
Author(s):  
Yue Wang ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Rui Wang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Optimal Policy ◽  
Practical Case ◽  
Battery Electric Vehicle ◽  
Battery Electric Vehicles ◽  
Endurance Range ◽  
Highway Network ◽  
Charging Stations ◽  
The Impact

The promotion of the battery electric vehicle has become a worldwide problem for governments due to its short endurance range and slow charging rate. Besides an appropriate network of charging facilities, a subsidy has proved to be an effective way to increase the market share of battery electric vehicles. In this paper, we investigate the joint optimal policy for a subsidy on electric vehicles and infrastructure construction in a highway network, where the impact of siting and sizing of fast charging stations and the impact of subsidy on the potential electric vehicle flows is considered. A new specified local search (LS)-based algorithm is developed to maximize the overall number of available battery electric vehicles in the network, which can get provide better solutions in most situations when compared with existed algorithms. Moreover, we firstly combined the existing algorithms to establish a multi-stage optimization method, which can obtain better solutions than all existed algorithms. A practical case from the highway network in Hunan, China, is studied to analyze the factors that impact the choice of subsidy and the deployment of charging stations. The results prove that the joint policy for subsidy and infrastructure construction can be effectively improved with the optimization model and the algorithms we developed. The managerial analysis indicates that the improvement on the capacity of charging facility can increase the proportion of construction fees in the total budget, while the improvement in the endurance range of battery electric vehicles is more efficient in expanding battery electric vehicle adoption in the highway network. A more detailed formulation of the battery electric vehicle flow demand and equilibrium situation will be studied in the future.

Impact of Residential and Public Charging Stations of Electric Vehicles on Distribution System by Stochastic Simulation

2015 ◽  
Vol 1092-1093 ◽  
pp. 375-380
Author(s):  
Suthida Ruayariyasub ◽  
Sompon Sirisumrannukul ◽  
Suksan Wangsatitwong
Keyword(s):  
Monte Carlo ◽  
Electric Vehicles ◽  
Distribution System ◽  
Stochastic Approach ◽  
Local Distribution ◽  
Battery Charging ◽  
Proposed Model ◽  
Charging Stations ◽  
The Impact

This paper investigates the impact of electric vehicles battery charging on the distribution system load if electric vehicles (EVs) are widespread used on roads. Stochastic approach based on a Monte Carlo method is developed in this study to simulate EVs charging load in two cases: 1) normal charge service at home, and 2) quick charge service at public charging stations. To demonstrate the model, a 22-kV distribution system of Pattaya City operated by Provincial Electricity Authority of Thailand (PEA) is employed in the case study. The results indicate the capability of the proposed model to exhibit the impact of EVs charging load on the local distribution system.

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 Electric Vehicle Charging System

2021 ◽  
pp. 92-96
Author(s):  
Rutuja Rajole ◽  
Rutuja Kakulte ◽  
Ashwin Pathak
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution Systems ◽  
Cost Effective ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
The World ◽  
Vehicle Charging ◽  
Charging Stations ◽  
The Impact

Electric vehicles are a new and upcoming technology in the transportation and power sector that have many benefits in terms of economic and environmental. This study presents a comprehensive review and evaluation of various types of electric vehicles and its associated equipment in particular battery charger and charging station. A comparison is made on the commercial and prototype electric vehicles in terms of electric range, battery size, charger power and charging time. The various types of charging stations and standards used for charging electric vehicles have been outlined and the impact of electric vehicle charging on utility distribution systems is also discussed. The methodology presented here was time-and cost-effective, as well as scalable to other organizations that own charging stations. Electric vehicles (EVs) are becoming increasingly popular in many countries of the world. EVs are proving more energy efficient and environmental friendly. But the lack of charging stations restricts the wide adoption of EVs in the world. As EV usage grows, more public spaces are installing EV charging stations.

scholarly journals Analysis of the impact of electric vehicles on the power grid

2018 ◽  
Vol 44 ◽  
pp. 00065 ◽  
Author(s):  
Leszek Kasprzyk ◽  
Robert Pietracho ◽  
Karol Bednarek
Keyword(s):  
Electric Vehicles ◽  
Transmission Lines ◽  
Power Distribution ◽  
Power Grid ◽  
Power Grids ◽  
Electric Vehicle Charging ◽  
Voltage Drops ◽  
Charging Stations ◽  
The Impact ◽  
Methods Of Control

The paper presents problems related to the impact of electric vehicles connected to the power grid on energy parameters. Basic methods of control in power grids were discussed and results of the simulation were presented with regards to the power distribution, voltage drops and losses in the transmission lines. The simulation was conducted based on the example of CIGRE 11, to which electric vehicle charging stations were connected in several selected points, with the possibility of energy release into the grid. The obtained results were compared for the simulation conducted in two variants – without the connected electric vehicles and with them. The obtained results were analyzed and commented upon.

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 Impact of Smart Charging for Consumers in a Real World Pilot

2020 ◽  
Vol 11 (1) ◽  
pp. 21 ◽  
Author(s):  
Pieter C. Bons ◽  
Aymeric Buatois ◽  
Guido Ligthart ◽  
Frank Geerts ◽  
Nanda Piersma ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Real World ◽  
Hybrid Electric Vehicles ◽  
Electricity Grid ◽  
Smart Charging ◽  
Maximum Current ◽  
Charging Stations ◽  
New Generation ◽  
The Impact ◽  
Ev Charging

A smart charging profile was implemented on 39 public charging stations in Amsterdam on which the current level available for electric vehicle (EV) charging was limited during peak hours on the electricity grid (07:00–08:30 and 17:00–20:00) and was increased during the rest of the day. The impact of this profile was measured on three indicators: average charging power, amount of transferred energy and share of positively and negatively affected sessions. The results are distinguished for different categories of electric vehicles with different charging characteristics (number of phases and maximum current). The results depend heavily on this categorisation and are a realistic measurement of the impact of smart charging under real world conditions. The average charging power increased as a result of the new profile and a reduction in the amount of transferred energy was detected during the evening hours, causing outstanding demand which was solved at an accelerated rate after limitations were lifted. For the whole population, 4% of the sessions were positively affected (charged a larger volume of energy) and 5% were negatively affected. These numbers are dominated by the large share of plug-in hybrid electric vehicles (PHEVs) in Amsterdam which are technically not able to profit from the higher current levels. For new generation electric vehicles, 14% of the sessions were positively affected and the percentage of negatively affected sessions was 5%.

scholarly journals Charging Station and Power Network Planning for Integrated Electric Vehicles (EVs)

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2595 ◽  
Author(s):  
Guozhong Liu ◽  
Li Kang ◽  
Zeyu Luan ◽  
Jing Qiu ◽  
Fenglei Zheng
Keyword(s):  
Case Studies ◽  
Traffic Flow ◽  
Electric Vehicles ◽  
Distribution System ◽  
Large Scale ◽  
Distribution Networks ◽  
Fuzzy Membership Function ◽  
Multi Objective ◽  
Charging Stations ◽  
The Impact

The optimal location and size of charging stations are important considerations in relation to the large-scale application of electric vehicles (EVs). In this context, considering that charging stations are both traffic service facilities and common electric facilities, a multi-objective model is built, with the objectives of maximizing the captured traffic flow in traffic networks and minimizing the power loss in distribution networks. There are two kinds of charging stations that are considered in this paper, and the planning of EV charge stations and distribution networks is jointly modelled. The formulated multi-objective optimization problem is handled by a fuzzy membership function. The genetic algorithm (GA) is used to solve the objective function. In case studies, a 33-node distribution system and a 25-node traffic network are used to verify the effectiveness of the proposed model. The location and capacity of two kinds of charging stations are designed in the case studies, after which the impact of the battery on the captured traffic flow is analyzed as well.

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