Long-Term Development Scale and Charging Load Forecasting of Electric Vehicle

2013 ◽  
Vol 448-453 ◽  
pp. 3194-3200
Author(s):  
Zi Long Cai ◽  
Hong Chun Shu
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Future Development ◽  
Load Forecasting ◽  
Distribution Grid ◽  
Electric Vehicle Charging ◽  
New Energy ◽  
Big City ◽  
New Energy Vehicle ◽  
Charging Stations

Because of the energy crisis and environment deterioration, there is a general consensus about the development of new energy vehicle especially electric vehicle in the world. The development of electric vehicles has brought new challenges to the distribution network. The charging strategy, the location planning of electric vehicle charging stations and sizing, the coordination planning between electric vehicle and the distribution grid depends on the future development scale electric vehicles and charging load forecasting. Because there is a certain distance from commercial operation in china, the prediction theory and method of the electric vehicle development scale and charging load are not mature. By using the method of artificial neural network to establish the development scale and charging load forecasting model of electric vehicle. The model is proved its correctness through an example of the electric vehicle scale and charging load forecasting of Kunming, a big city in West China. The paper provides a new way for future development scale and charging load forecasting to electric vehicle of China.

Negative Impacts on the Smart Distribution Grid Caused by New Energy

2015 ◽  
Vol 1092-1093 ◽  
pp. 463-466
Author(s):  
Li Jun Qin ◽  
Wan Tao Yang
Keyword(s):  
Smart Grid ◽  
Electric Vehicle ◽  
Distribution Network ◽  
Distribution Grid ◽  
Electric Vehicle Charging ◽  
New Energy ◽  
Vehicle Charging ◽  
Smart Distribution Grid ◽  
Charging Stations ◽  
The Impact

The access problem of new energy is one of the core content of the smart grid. New energy such as wind, solar, electric vehicle charging stations have strong intermittent and fluctuations. Their technical performance is poor to access to the grid.They inject harmonics into grid and have other issues. This paper describes the impact on the distribution network after the wind, photovoltaic power generation, electric vehicle charging stations connected to the grid.It is hoped that you can build smart grid distribution model,research in-depth and analysis the combined effects of smart distribution grid after new energy sources accessed, to achieve the monitoring of the various components of the distribution network and the best combination for electricity.

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.

scholarly journals Distribution Network Congestion Dispatch Considering Time-Spatial Diversion of Electric Vehicles Charging

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2820 ◽  
Author(s):  
Hui Sun ◽  
Peng Yuan ◽  
Zhuoning Sun ◽  
Shubo Hu ◽  
Feixiang Peng ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution Network ◽  
Network Congestion ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Large Numbers ◽  
Pricing Scheme ◽  
Multiple Charging ◽  
Charging Stations

With the popularization of electric vehicles, free charging behaviors of electric vehicle owners can lead to uncertainty about charging in both time and space. A time-spatial dispatching strategy for the distribution network guided by electric vehicle charging fees is proposed in this paper, which aims to solve the network congestion problem caused by the unrestrained and free charging behaviors of large numbers of electric vehicles. In this strategy, congestion severity of different lines is analyzed and the relationship between the congested lines and the charging stations is clarified. A price elastic matrix is introduced to reflect the degree of owners’ response to the charging prices. A pricing scheme for optimal real-time charging fees for multiple charging stations is designed according to the congestion severity of the lines and the charging power of the related charging stations. Charging price at different charging station at different time is different, it can influence the charging behaviors of vehicle owners. The simulation results confirmed that the proposed congestion dispatching strategy considers the earnings of the operators, charging cost to the owners and the satisfaction of the owners. Moreover, the strategy can influence owners to make judicious charging plans that help to solve congestion problems in the network and improve the safety and economy of the power grid.

scholarly journals Simulation of Future Electric Vehicle Charging Behavior—Effects of Transition from PHEV to FEV

2019 ◽  
Vol 10 (2) ◽  
pp. 42 ◽  
Author(s):  
Igna Vermeulen ◽  
Jurjen Rienk Helmus ◽  
Mike Lees ◽  
Robert van den Hoed
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Early Years ◽  
Charging Infrastructure ◽  
Agent Based ◽  
Electric Vehicle Charging ◽  
Subsidy Scheme ◽  
Infrastructure Performance ◽  
Charging Stations

The Netherlands is a frontrunner in the field of public charging infrastructure, having one of the highest number of public charging stations per electric vehicle (EV) in the world. During the early years of adoption (2012–2015), a large percentage of the EV fleet were plugin hybrid electric vehicles (PHEV) due to the subsidy scheme at that time. With an increasing number of full electric vehicles (FEVs) on the market and a current subsidy scheme for FEVs only, a transition of the EV fleet from PHEV to FEV is expected. This is hypothesized to have an effect on the charging behavior of the complete fleet, and is reason to understand better how PHEVs and FEVs differ in charging behavior and how this impacts charging infrastructure usage. In this paper, the effects of the transition of PHEV to FEV is simulated by extending an existing agent-based model. Results show important effects of this transition on charging infrastructure performance.

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 Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2692 ◽  
Author(s):  
Juncheng Zhu ◽  
Zhile Yang ◽  
Monjur Mourshed ◽  
Yuanjun Guo ◽  
Yimin Zhou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Comparative Study ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Load Forecasting ◽  
Learning Approaches ◽  
Short Term ◽  
Learning Methods ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Load forecasting is one of the major challenges of power system operation and is crucial to the effective scheduling for economic dispatch at multiple time scales. Numerous load forecasting methods have been proposed for household and commercial demand, as well as for loads at various nodes in a power grid. However, compared with conventional loads, the uncoordinated charging of the large penetration of plug-in electric vehicles is different in terms of periodicity and fluctuation, which renders current load forecasting techniques ineffective. Deep learning methods, empowered by unprecedented learning ability from extensive data, provide novel approaches for solving challenging forecasting tasks. This research proposes a comparative study of deep learning approaches to forecast the super-short-term stochastic charging load of plug-in electric vehicles. Several popular and novel deep-learning based methods have been utilized in establishing the forecasting models using minute-level real-world data of a plug-in electric vehicle charging station to compare the forecasting performance. Numerical results of twelve cases on various time steps show that deep learning methods obtain high accuracy in super-short-term plug-in electric load forecasting. Among the various deep learning approaches, the long-short-term memory method performs the best by reducing over 30% forecasting error compared with the conventional artificial neural network model.

Study on the Harmonic Impact of Large Scale Electric Vehicles to Grid

2013 ◽  
Vol 443 ◽  
pp. 273-278 ◽  
Author(s):  
Ceng Ceng Hao ◽  
Yue Jin Tang ◽  
Jing Shi
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Large Scale ◽  
Flow Distribution ◽  
Electric Grid ◽  
Nonlinear Loads ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations ◽  
Harmonic Problem

Large scale electric vehicles integration into power grid, as nonlinear loads, will pose inevitable impacts on the operation of power system, one of which the harmonic problem will affect the power quality greatly. Firstly, the article analyzes the characteristics of harmonic caused by electric vehicle charging. And then, the harmonic flow distribution is analyzed based on the IEEE standard node systems. During transient analyses, the electric vehicle charging stations connected to electric grid are represented as harmonic sources. Results show that structure and voltage grade of electric grid, capacity and access points of electric vehicle charging load will have different effects on harmonic problem. At last, a few conclusions are given for connecting electric vehicles to electric grid.

scholarly journals Novel Fuzzy Controller for a Standalone Electric Vehicle Charging Station Supplied by Photovoltaic Energy

2021 ◽  
Vol 4 (3) ◽  
pp. 63
Author(s):  
Sherif A. Zaid ◽  
Hani Albalawi ◽  
Khaled S. Alatawi ◽  
Hassan W. El-Rab ◽  
Mohamed E. El-Shimy ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Controller ◽  
Electric Utility ◽  
Low Noise ◽  
System Response ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

The electric vehicle (EV) is one of the most important and common parts of modern life. Recently, EVs have undergone a big development thanks to the advantages of high efficiency, negligible pollution, low maintenance, and low noise. Charging stations are very important and mandatory services for electric vehicles. Nevertheless, they cause high stress on the electric utility grid. Therefore, renewable energy-sourced charging stations have been introduced. They improve the environmental issues of the electric vehicles and support remote area operation. This paper proposes the application of fuzzy control to an isolated charging station supplied by photovoltaic power. The system is modeled and simulated using Matlab/Simulink. The simulation results indicate that the disturbances in the solar insolation do not affect the electric vehicle charging process at all. Moreover, the controller perfectly manages the stored energy to compensate for the solar energy variations. Additionally, the system response with the fuzzy controller is compared to that with the PI controller. The comparison shows that the fuzzy controller provides an improved response.

Feasibility Study of Renewable Energy Integrated Electric Vehicle Charging Infrastructure

2016 ◽  
pp. 313-349
Author(s):  
Azhar Ul-Haq ◽  
Marium Azhar
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Area Network ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

This chapter presents a detailed study of renewable energy integrated charging infrastructure for electric vehicles (EVs) and discusses its various aspects such as siting requirements, standards of charging stations, integration of renewable energy sources for powering up charging stations and interfacing devices between charging facilities and smart grid. A smart charging station for EVs is explained along with its essential components and different charging methodologies are explained. It has been recognized that the amalgamation of electric vehicles in the transportation sector will trigger power issues due to the mobility of vehicles beyond the stretch of home area network. In this regard an information and communication technology (ICT) based architecture may support EVs management with an aim to enhance the electric vehicle charging and energy storage capabilities with the relevant considerations. An ICT based solution is capable of monitoring the state of charge (SOC) of EV batteries, health and accessible amount of energy along with the mobility of EVs.

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