Deploying public charging stations for battery electric vehicles on the expressway network based on dynamic charging demand

2022 ◽  
pp. 1-1
Author(s):  
Tian-yu Zhang ◽  
Yang Yang ◽  
Yu-ting Zhu ◽  
En-jian Yao ◽  
Ke-qi Wu
Keyword(s):  
Electric Vehicles ◽  
Battery Electric Vehicles ◽  
Dynamic Charging ◽  
Charging Stations ◽  
Charging Demand

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.

scholarly journals Price effect analysis and pre-reseravtion scheme on electric vehicle charging networks

2019 ◽  
Vol 9 (6) ◽  
pp. 5586
Author(s):  
Junghoon Lee ◽  
Gyung-Leen Park
Keyword(s):  
Electric Vehicles ◽  
Service Providers ◽  
Real Life ◽  
Price Effect ◽  
Effect Analysis ◽  
Electric Vehicle Charging ◽  
Demand Patterns ◽  
Charging Stations ◽  
Occupancy Rates ◽  
Charging Demand

<p>This paper investigates the price effect to the charging demand coming from electric vehicles and then evaluates the performance of a pre-reservation mechanism using the real-life demand patterns. On the charging network in Jeju city, the occupancy rates for 3 price groups, namely, free, medium-price, and expensive chargers, are separated almost evenly by about 9.0 %, while a set of chargers dominates the charging demand during hot hours. The virtual pre-reservation scheme matches electric vehicles to a time slot of a charger so as not only to avoid intolerable waiting time in charging stations systematically but also to increase the revenue of service providers, taking into account both bidding levels specified by electric vehicles and preference criteria defined by chargers. The performance analysis results obtained by prototype implementation show that the proposed pre-reservation mechanism improves the revenue of service providers by up to 9.5 % and 42.9 %, compared with the legacy FCFS and reservation-less walk-in schemes for the given performance parameter sets.</p>

scholarly journals Deploying Electric Vehicle Charging Stations Considering Time Cost and Existing Infrastructure

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2436 ◽  
Author(s):  
Yuan Qiao ◽  
Kaisheng Huang ◽  
Johannes Jeub ◽  
Jianan Qian ◽  
Yizhou Song
Keyword(s):  
Electric Vehicles ◽  
Optimization Algorithm ◽  
Central Area ◽  
Time Cost ◽  
Battery Electric Vehicles ◽  
Electric Vehicle Charging ◽  
Service Areas ◽  
Harsh Criticism ◽  
The Right ◽  
Charging Stations

Under the challenge of climate change, fuel-based vehicles have been receiving increasingly harsh criticism. To promote the use of battery electric vehicles (BEVs) as an alternative, many researchers have studied the deployment of BEVs. This paper proposes a new method to choose locations for new BEV charging stations considering drivers’ perceived time cost and the existing infrastructure. We construct probability equations to estimate drivers’ demanding time for charging (and waiting to charge), use the Voronoi diagram to separate the study area (i.e., Shanghai) into service areas, and apply an optimization algorithm to deploy the charging stations in the right locations. The results show that (1) the probability of charging at public charging stations is 39.6%, indicating BEV drivers prefer to charge at home; (2) Shanghai’s central area and two airports have the busiest charging stations, but drivers’ time costs are relatively low; and (3) our optimization algorithm successfully located two new charging stations surrounding the central area, matching with our expectations. This study provides a time-efficient way to decide where to build new charging stations to improve the existing infrastructure.

scholarly journals Selecting Locations of Electric Vehicle Charging Stations Based on the Traffic Load Eliminating Method

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1650 ◽  
Author(s):  
Bong-Gi Choi ◽  
Byeong-Chan Oh ◽  
Sungyun Choi ◽  
Sung-Yul Kim
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Traffic Load ◽  
Queueing Model ◽  
Traffic Data ◽  
Electric Vehicle Charging ◽  
Supply Equipment ◽  
Charging Stations ◽  
Ev Charging ◽  
Charging Demand

Establishing electric vehicle supply equipment (EVSE) to keep up with the increasing number of electric vehicles (EVs) is the most realistic and direct means of promoting their spread. Using traffic data collected in one area; we estimated the EV charging demand and selected priority fast chargers; ranging from high to low charging demand. A queueing model was used to calculate the number of fast chargers required in the study area. Comparison of the existing distribution of fast chargers with that suggested by the traffic load eliminating method demonstrated the validity of our traffic-based location approach.

scholarly journals Macro Study of Global Electric Vehicle Expansion

2021 ◽  
Vol 15 (1) ◽  
pp. 67-73
Author(s):  
Thakur Dhakal ◽  
◽  
Kyoung-Soon Min ◽  
Keyword(s):  
European Union ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Bass Model ◽  
The European Union ◽  
Sales Data ◽  
Battery Electric Vehicles ◽  
The World ◽  
Charging Stations ◽  
The Eu

This study analyzes the diffusion of battery electric vehicles (BEV) in the world and evaluates the vehicle charging stations based on the European Union (EU) scenario. Initially, the global BEV sales data from 2005 to 2018 are fitted with the two most frequently used econometric logistics and Bass diffusion models. Further, the study identifies the different stage adopters, forecasts the consumption of BEVs, and examines the velocity and acceleration of BEV diffusion. Finally, future charging stations are examined to meet the BEV sales demand. Results suggest that the adoption of BEVs demonstrates a better fit on the Bass model where the global BEV market is estimated to grow from 5,3 millions in 2019 to near 40 millions units by 2030, and with the reference of the EU countries’ adoption scenario, the global charging stations will be increased from near 2 millions in 2019 to near 10 millions units by 2030.

scholarly journals Locating Charging Stations of Various Sizes with Different Numbers of Chargers for Battery Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3056 ◽  
Author(s):  
Shaohua Cui ◽  
Hui Zhao ◽  
Cuiping Zhang
Keyword(s):  
Electric Vehicles ◽  
Location Problem ◽  
Capacity Constraints ◽  
Sustainable Transportation ◽  
Market Potential ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Link Capacity ◽  
Battery Electric Vehicles ◽  
Charging Stations

Compared with traditional fuel vehicles, battery electric vehicles (BEVs) as a sustainable transportation form can reduce carbon dioxide emissions and save energy, so its market share has great potential. However, there are some problems, such as: Their limited range, long recharging time, and scarce charging facilities, hindering improvement in the market potential of BEVs. Therefore, perfect and efficient charging facility deployment for BEVs is very important. For this reason, the optimal locations for charging stations for BEVs are investigated in this paper. Instead of flow-based formulation, this paper is based on agents under strictly imposed link capacity constraints, where all agents can select their routes and decide on the battery recharging plan without running out of charge. In our study, not only the locations of charging stations, but also the size of charging stations with the different number of chargers, would be taken into consideration. Then, this problem is formulated as a location problem for BEV charging stations of multiple sizes based on agents under link capacity constraints. This problem is referred to as the agent-refueling, multiple-size location problem with capacitated network (ARMSLP-CN). We formulate the ARMSLP-CN as a 0–1 mixed-integer linear program (MILP) with the aim to minimize the total trip time for all agents, including four parts, namely, the travel time, queue time, fixed time for recharging, and variable recharging time depending on the type of charger and the amount of power recharged, in which commercial solvers can solve the linearized model directly. To demonstrate this model, two different numerical instances are designed, and sensitivity analyses are also presented.

scholarly journals Analyzing the Fast-Charging Potential for Electric Vehicles with Local Photovoltaic Power Production in French Suburban Highway Network

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2428
Author(s):  
Abood Mourad ◽  
Martin Hennebel ◽  
Ahmed Amrani ◽  
Amira Ben Hamida
Keyword(s):  
Electric Vehicles ◽  
Production Costs ◽  
Heavy Trucks ◽  
Fast Charging ◽  
Highway Network ◽  
Data Driven Approach ◽  
Charging Stations ◽  
Ev Charging ◽  
Charging Demand

The need for deploying fast-charging stations for electric vehicles (EVs) is becoming essential in recent years. This need is justified by the increasing charging demand and supported by new charging technologies making EV chargers more efficient. In this paper, we provide a survey on EV fast-charging models and introduce a data-driven approach with an optimization model for deploying EV fast-chargers for both electric vehicles and heavy trucks traveling through a network of suburban highways. This deployment aims at satisfying EV charging demands while respecting the limits imposed by the electric grid. We also consider the availability of local photovoltaic (PV) farm and integrate its produced power to the proposed charging network. Finally, through a case study on Paris-Saclay area, we provide locations for EV charging stations and analyze the benefits of integrating PV power at different prices, production costs and charging capacities. The obtained results also suggest potential enhancements to the charging network in order to accommodate the increasing charging demand for EVs in the future.

An Incentive-Compatible Combinatorial Auction Design for Charging Network Scheduling of Battery Electric Vehicles

2021 ◽  
pp. 1-18
Author(s):  
Luyang Hou ◽  
Chun Wang ◽  
Jun Yan
Keyword(s):  
New York ◽  
Electric Vehicles ◽  
Dominant Strategy ◽  
Combinatorial Auction ◽  
Network Scheduling ◽  
Winner Determination ◽  
Incentive Compatible ◽  
Battery Electric Vehicles ◽  
Energy Demands ◽  
Charging Stations

Charging network scheduling for battery electric vehicles is a challenging research issue on deciding where and when to activate users’ charging under the constraints imposed by their time availability and energy demands, as well as the limited available capacities provided by the charging stations. Moreover, users’ strategic behaviors and untruthful revelation on their real preferences on charging schedules pose additional challenges to efficiently coordinate their charging in a market setting, where users are reasonably modelled as self-interested agents who strive to maximize their own utilities rather than the system-wide efficiency. To tackle these challenges, we propose an incentive-compatible combinatorial auction for charging network scheduling in a decentralized environment. In such a structured framework, users can bid for their preferred destination and charging time at different stations, and the scheduling specific problem solving structure is also embedded into the winner determination model to coordinate the charging at multiple stations. The objective is to maximize the social welfare across all users which is represented by their total values of scheduled finishing time. The Vickrey–Clarke–Groves payment rule is adopted to incentivize users to truthfully disclose their true preferences as a weakly dominant strategy. Moreover, the proposed auction is proved to be individually rational and weakly budget balanced through an extensive game-theoretical analysis. We also present a case study to demonstrate its applicability to real-world charging reservation scenarios using the charging network data from Manhattan, New York City.

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