scholarly journals Charging Load Allocation Strategy of EV Charging Station Considering Charging Mode

2019 ◽  
Vol 10 (2) ◽  
pp. 47 ◽  
Author(s):  
Yutong Zhao ◽  
Hong Huang ◽  
Xi Chen ◽  
Baoqun Zhang ◽  
Yiguo Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Allocation Strategy ◽  
Charging Station ◽  
Charging Mode ◽  
Grid Load ◽  
Coordinated Charging ◽  
Charging Stations ◽  
Additional Service ◽  
Ev Charging ◽  
Scale Grid

A charging load allocation strategy for Electric Vehicles (EVs) considering charging mode is proposed in this paper in order to solve the challenge and opportunity of large-scale grid-connected charging under the background of booming EV industry in recent years. Based on the peak-to-valley Time-of-Use (TOU) price, this strategy studies the grid load, charging cost and charging station revenue variation of EVs connected to the grid in different charging modes. In addition, this paper proposes an additional charging mechanism for charging stations to encourage EV owners to participate in the peak and valley reduction of the grid through coordinated charging. According to the example analysis, under the same charging demand conditions, the larger EV charging power will have a greater impact on the grid than the conventional charging power. This article collects additional service fees for car owners who are not involved in the coordinated charging. When the response charging ratio is less, the more total service charges are charged, which can compensate for the decline in the sales revenue of the charging station during the valley period. While having good economy, it can also encourage the majority of car owners to participate in the coordinated charging from the perspective of charging cost.

Electric Vehicle Charging Station Load Forecasting and Impact of the Load Curve

2012 ◽  
Vol 229-231 ◽  
pp. 853-858 ◽  
Author(s):  
Jian Wang ◽  
Kui Hua Wu ◽  
Feng Wang ◽  
Zhi Hui Li ◽  
Qing Song Niu ◽  
...  
Keyword(s):  
Power Grid ◽  
Paper Briefly ◽  
Load Curve ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Charging Mode ◽  
Resistive Model ◽  
Coordinated Charging ◽  
Charging Stations ◽  
Daily Load

With the popularity of electric vehicles, a large number of charging stations connected to the grid, will bring about tremendous influence on the power, voltage and current of grid. This paper briefly introduces several common types of charging mode, and analyzes the characteristics of them. According to statistics, a resistive model of charging stations, simulating the regional power grid with a IEEE34 node model, has been established to forecast the daily load curve, using Monte Carlo simulation. An analysis is performed for a power grid to demonstrate the impacts of the daily load curve considering different power of charging stations, which are under coordinated charging conditions, to indicate the harm of uncoordinated charging and put forward solutions.

scholarly journals Self-Sustainable off grid Electric Vehicle (EV) Charging Station with Integration of Renewable Sources

2020 ◽  
Vol 9 (3) ◽  
pp. 2669-2674
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Large Scale ◽  
Transport Systems ◽  
Diesel Generator ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Power Generation Technology ◽  
Charging Stations ◽  
Ev Charging

Electric Vehicles (EV) are the world’s future transport systems. With the rise in pollutions and its effects on the environment, there has been a large scale movetowards electrical vehicles. But the plug point availability for charging is the serious problem faced by the mostof Electric Vehicle consumers. Therefore, there is a definite need to move from the GRID based/connected charging stations to standalone off-grid stations for charging the Electric Vehicles. The objective of this paper is to arrive at the best configuration or mix of the renewable resources and energy storage systems along with conventional Diesel Generator set which together works in offgrid for Electric Vehicle charging. As aconclusion, by utilizing self-sustainable off-grid power generation technology, the availability of EV charging stations in remote localities at affordable price can be made and mainly it reduces burden on the existing electrical infrastructure.

scholarly journals Blockchain-Enabled Charging Right Trading Among EV Charging Stations

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3922 ◽  
Author(s):  
Ruijiu Jin ◽  
Xiangfeng Zhang ◽  
Zhijie Wang ◽  
Wengang Sun ◽  
Xiaoxin Yang ◽  
...  
Keyword(s):  
Power Systems ◽  
Power Transmission ◽  
Charging Station ◽  
Double Auctions ◽  
Incentive Compatible ◽  
Trading Mechanism ◽  
Charging Stations ◽  
Trading Simulation ◽  
Ev Charging ◽  
Charging Demand

Increasing penetration of electric vehicles (EVs) gives rise to the challenges in the secure operation of power systems. The EV charging loads should be distributed among charging stations in a fair and incentive-compatible manner while ensuring that power transmission and transformation facilities are not overloaded. This paper first proposes a charging right (or charging power ration) trading mechanism and model based on blockchain. Considering all kinds of random factors of charging station loads, we use Monte Carlo modeling to determine the charging demand of charging stations in the future. Based on the charging demand of charging stations, a charging station needs to submit the charging demand for a future period. The blockchain first distributes initial charging right in a just manner and ensures the security of facilities. Given that the charging urgency and elasticity differences vary by charging stations, all charging stations then proceed with double auction and peer-to-peer (P2P) transaction of charging right. Bids and offers are cleared via double auctions if bids are higher than offers. The remaining bids and offers are cleared via the P2P market. Then, this paper designs the charging right allocation and trading platform and smart contract based on the Ethernet blockchain to ensure the safety of the distribution network (DN) and the transparency and efficiency of charging right trading. Simulation results based on the Ethereum private blockchain show the fairness and efficiency of the proposed mechanism and the effectiveness of the method and the mechanism.

Load Forecasting of Charging and Swapping in Large-Scale Electric Vehicle

2014 ◽  
Vol 568-570 ◽  
pp. 1969-1977 ◽  
Author(s):  
Jian Cheng Ye ◽  
Yu Ling Li ◽  
Dong Liang Zhang ◽  
Xiang Jing Zhu ◽  
Jin Da Zhu
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Access Network ◽  
Calculation Model ◽  
Simulation Algorithm ◽  
Charging Time ◽  
Load Calculation ◽  
Other Information ◽  
Charging Mode ◽  
Ev Charging

This article combs the charging mode of electric vehicle,and analyzes different charging ways for buses,taxis and sedans,thereby drawing their appropriate charging time and characteristics of the interaction with grid. The paper establishes the load calculation model for the charging and swapping in Evs respectively. The load calculation model divides one day into 1440 minutes, and use the Monte Carlo simulation algorithm to extract the initial SOC, the initial charging time and other information for load calculation and analyze the EV charging load. The results show that the charging load of electric vehicle has obvious difference between peak and vally,and provide reference for the management and policy oriented electric vhicle access network.

Research on EV Ordered Charging Considering TOU Price

2013 ◽  
Vol 448-453 ◽  
pp. 3147-3153
Author(s):  
Mai Zhang ◽  
Cai Hong Zhao ◽  
Li Juan Tan ◽  
Li Liu ◽  
Lu Lu Chen
Keyword(s):  
Large Scale ◽  
User Behavior ◽  
User Behavior Analysis ◽  
User Charge ◽  
Charging Mode ◽  
Simulation Results ◽  
Grid Operation ◽  
The Cost ◽  
Load Stability ◽  
Ev Charging

Large-scale of electric vehicles (EVs) for charging will affect grid operation, disordered charging will have significant impact on the grid. This paper presents ordered charging mathematical model considering the smallest charging fees for EV users, a genetic algorithm is used to get optimization solutions. Monte Carlo method is used to simulate EV charging user behavior, analysis of disordered and ordered charging simulation results are compared under different charging mode. Simulation results show that ordered charging has huge roles in reducing the cost of user charge, reducing the peak-valley difference, improving load stability and users satisfaction. The results of example show the rationality of this model and algorithm.

Discussion on the Mode of Electric Vehicle Power Supply Infrastructures Construction and Operation in China

2011 ◽  
Vol 347-353 ◽  
pp. 3902-3907
Author(s):  
Liang Liang Chen ◽  
Ming Wu ◽  
Hao Zhang ◽  
Xiao Hua Ding ◽  
Jin Da Zhu
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Power Supply ◽  
Energy Supply ◽  
Large Scale ◽  
Operation Mode ◽  
Charging Station ◽  
Combination Mode ◽  
Ev Charging

The energy supply infrastructures construction is the prerequisite and basis for the large-scale promotion and application of electric vehicles (EVs). The characteristics and current construction situation of several EV power supply infrastructures in China such as AC charging spot, charging station and battery swap station are introduced first, and the characteristics of time combination mode and space combination mode for the construction of EV charging facilities are also discussed. Meanwhile, the features of operation mode for EV power supply infrastructures in different developing stage of are analyzed, and the main bodies for EV power supply infrastructures construction are also introduced.

A Guided Particle Swarm Optimizer for Distributed Operation of Electric Vehicle to Building Integration

2017 ◽  
Author(s):  
Yang Chen ◽  
Mengqi Hu
Keyword(s):  
Private Information ◽  
Large Scale ◽  
Particle Swarm ◽  
Commercial Building ◽  
Particle Swarm Optimizer ◽  
Charging Station ◽  
Solution Strategies ◽  
Ev Charging ◽  
Marginal Price ◽  
Distributed Decision

Relevant research has demonstrated that more potential benefits can be achieved when energy and information are transacted and exchanged locally among different energy consumers. With increasing number of electric vehicles (EVs), various models and solution strategies have been developed for collaboration between building and EV charging station to achieve greater energy efficiency. However, most of the existing research employs centralized decision model which is time consuming for large scale problems and cannot protect private information for each participator. To bridge these research gaps, a guided particle swarm optimizer based distributed decision approach is proposed to study the energy transaction between building and EV charging station. In the proposed decision approach, the marginal price signal of transactive energy is collected to guide iterative direction of particle’s velocity and position which can maximally protect private information of building and EV charging station. A study case based on a commercial building and a nearby charging station in Chicago area is designed for illustration. The experimental results demonstrate that our proposed marginal price guided particle swarm optimizer is more stable and efficient comparing with canonical particle swarm optimizer and two state-of-the-art distributed decision algorithms.

scholarly journals A smart management system of electric vehicles charging plans on the highway charging stations

2021 ◽  
Vol 23 (2) ◽  
pp. 752
Author(s):  
Ibrahim El-Fedany ◽  
Driss Kiouach ◽  
Rachid Alaoui
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Long Distance ◽  
Smart Transportation ◽  
Charging Station ◽  
Charging Time ◽  
Trip Time ◽  
Automatic Mechanism ◽  
Charging Stations

Electric vehicles (EVs) are seen as one of the principal pillars of smart transportation to relieve the airborne pollution induced by fossil CO2 emissions. However, the battery limit, especially where the journey is with a long-distance road remains the most formidable obstacle to the large-scale use of EVs. To overcome the issue of prolonged waiting charging time due to the large number of EVs may have a charging plan at the same charging station (CS) along the highway, we propose a communication system to manage the EVs charging demands. The architecture system contains a smart scheduling algorithm to minimize trip time including waiting time, previous reservations and energyare needed to reach the destination. Moreover, an automatic mechanism for updating reservation is integrated to adjust the EVs charging plans. The results of the evaluation under the Moroccan highway scenario connecting Rabat and Agadir show the effectiveness of our proposal system.<br /><div> </div>

scholarly journals An Orderly EV Charging Scheduling Method Based on Deep Learning in Cloud-Edge Collaborative Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jiayong Zhong ◽  
Xiaofu Xiong
Keyword(s):  
Distribution Network ◽  
Operating Cost ◽  
Safe Operation ◽  
Charging Station ◽  
Collaborative Environment ◽  
Scheduling Method ◽  
Load Peak ◽  
Residential Distribution ◽  
Charging Stations ◽  
Ev Charging

The rapid increase of the number of electric vehicles (EVs) has posed great challenges to the safe operation of the distribution network. Therefore, this paper proposes an ordered charging scheduling method for EV in the cloud-edge collaborative environment. Firstly, the uncertainty of user load demands, charging station requirements, and renewable outputs are taken into consideration. Correspondingly, the residential distribution points, EV charging stations, and renewable plants are regarded as the edge nodes. Then, the load demands and renewable outputs are predicted by a model combined with the convolutional neural network and deep belief network (CNN-DBN). Secondly, the power supply plans for charging stations are determined at the cloud side aiming at minimizing the operating cost of the distribution network via collecting the forecasting results. Finally, the charging station formulates the personalized charging scheduling strategies according to EV’s charging plans and the charging demands in order to follow the supply plan. The simulation results show that the load peak-to-valley difference and standard deviation of the proposed algorithm are reduced by 30.13% and 16.94%, respectively, compared with the disorderly charging and discharging behavior, which has verified the effectiveness and feasibility of the proposed method.

Impact of Electric Vehicle Charging Mode on Load Characteristic in the Shandong Electric Power Grid

2012 ◽  
Vol 608-609 ◽  
pp. 1582-1586
Author(s):  
Jian Wang ◽  
Kui Hua Wu ◽  
Feng Wang ◽  
Kui Zhong Wu ◽  
Zhi Zhen Liu
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Power Grid ◽  
Maximum Load ◽  
Load Models ◽  
Electric Vehicle Charging ◽  
Electric Power Grid ◽  
Charging Mode ◽  
Ev Charging ◽  
Storage Property

The large scale development of electric vehicle will have both benefits and potential stresses on power grid. It is shown that uncoordinated charging of EVs’ on the grid will produce series of problems, while intelligent charging can improve the operation of the power grid. In this study, based on several scenarios of charging modes, such as plug and charge, night charging and intelligent charging, the corresponding EV load models have been established. Therefore, an analysis is performed for the load characteristics of Shandong power grid to demonstrate the impacts of different EV charging scenarios. The results demonstrate that rational utilization of EVs’ load and energy storage property can help to decrease the maximum load of grid and the peak-valley difference, to stable load, and to raise the utilization of the power facilities.

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