Research on Load Modeling of Electric Vehicles

2013 ◽  
Vol 291-294 ◽  
pp. 892-897
Author(s):  
Jian Lei Fan ◽  
Jun Liu ◽  
Lei Zhang ◽  
Hong Peng He
Keyword(s):  
Electric Vehicle ◽  
Dynamic Model ◽  
Dynamic Stability ◽  
Electric Vehicles ◽  
Load Modeling ◽  
Load Model ◽  
Modeling Approach ◽  
Electric Vehicle Charging ◽  
Static And Dynamic Stability ◽  
Composite Load Model

The accurate electric vehicle charging load model shall be established to analyze potential challenges of static and dynamic stability brought by electric vehicles. In this paper, experiments with the electric vehicle charger and battery were carried out to analyze the model characteristics. And then this model was compared to the composite load model. At last, the modeling approach of static and dynamic model of electric vehicles was proposed.

scholarly journals Electric Vehicle Charging Load Model Based on Diffusion Theory

2014 ◽  
Vol 8 (1) ◽  
pp. 954-959
Author(s):  
Han Peng ◽  
Jinmei Wu ◽  
Lu Wang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Diffusion Theory ◽  
Load Curve ◽  
Load Model ◽  
Electric Vehicle Charging ◽  
Actual Application ◽  
Single Vehicle ◽  
Lower Load ◽  
Vehicle Charging

Purpose: discuss actual application value of the diffusion theory in massive electric vehicle charging load. Method: introduce single vehicle charging process, extend it to charging process of two and multiple electric vehicles, abstract physical process of parallel charging of electric vehicles, introduce energy block concept and diffusion theory, and establish diffusion charging model of electric vehicles based on them. Results: computing results of the charging load of multiple electric vehicles indicates that the computing results of the diffusion load model of electric vehicles feature better continuity and lower load compared to the computing results of the Monte Carlo load model. The charging load curve of private vehicles shows double peaks on the business days. The charging load of vehicles reduces at the weekend and shows single-peak curve. Conclusion: the computing results validate effectivity of the diffusion theory in charging model of multiple electric vehicles, which is worthy of further research in industrialization process.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

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 An Optimal Control Algorithm with Reduced DC-Bus Current Fluctuation for Multiple Charging Modes of Electric Vehicle Charging Station

2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Current Fluctuation ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Three Phase ◽  
Optimization Control ◽  
Dc Bus ◽  
Vehicle Charging

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.

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.

Development of the Power Load Modeling System with Denoising and Parameter Identification

2013 ◽  
Vol 805-806 ◽  
pp. 712-715
Author(s):  
Li Di Wang ◽  
Qing Ying Ge ◽  
Zhe Li ◽  
Tai Gang Nian
Keyword(s):  
Parameter Identification ◽  
Dynamic Model ◽  
Variable Load ◽  
Signal Acquisition ◽  
Load Modeling ◽  
Load Model ◽  
Process Measurement ◽  
Power Load ◽  
Measurement Signal ◽  
Zip Model

The power load modeling system is designed with denoising and parameter identification. This system consists of signal acquisition, signal preprocessing, parameter identification, different load modeling methods such as ZIP model and Dynamic modeling. Original signal can be read from Excel file, which is the simulated signal or measurement signal. Then some kinds of denoising methods can be selected, which are mean filtering, medial filtering and wavelet denoising. After being denoised, the load signal is suitable for the parameter identification process. ZIP model is used to simulate the static load model, and the dynamic model is used to simulate the dynamic load model which is changeable during different periods. With the parameter identification and simulation process, measurement power load signal is used in the experiment, the dynamic model is more suitable for the variable load voltage features description.

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 Efficient Gear Ratio Selection of a Single-Speed Drivetrain for Improved Electric Vehicle Energy Consumption

2020 ◽  
Vol 12 (21) ◽  
pp. 9254
Author(s):  
Polychronis Spanoudakis ◽  
Gerasimos Moschopoulos ◽  
Theodoros Stefanoulis ◽  
Nikolaos Sarantinoudis ◽  
Eftichios Papadokokolakis ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Dynamic Model ◽  
Electric Vehicles ◽  
Gear Ratio ◽  
Test Bed ◽  
Time Data ◽  
Dynamic Simulations ◽  
Ratio Set ◽  
Selection Of

The electric vehicle (EV) market has grown over the last few years and even though electric vehicles do not currently possess a high market segment, it is projected that they will do so by 2030. Currently, the electric vehicle industry is looking to resolve the issue of vehicle range, using higher battery capacities and fast charging. Energy consumption is a key issue which heavily effects charging frequency and infrastructure and, therefore, the widespread use of EVs. Although several factors that influence energy consumption of EVs have been identified, a key technology that can make electric vehicles more energy efficient is drivetrain design and development. Based on electric motors’ high torque capabilities, single-speed transmissions are preferred on many light and urban vehicles. In the context of this paper, a prototype electric vehicle is used as a test bed to evaluate energy consumption related to different gear ratio usage on single-speed transmission. For this purpose, real-time data are recorded from experimental road tests and a dynamic model of the vehicle is created and fine-tuned using dedicated software. Dynamic simulations are performed to compare and evaluate different gear ratio set-ups, providing valuable insights into their effect on energy consumption. The correlation of experimental and simulation data is used for the validation of the dynamic model and the evaluation of the results towards the selection of the optimal gear ratio. Based on the aforementioned data, we provide useful information from numerous experimental and simulation results that can be used to evaluate gear ratio effects on electric vehicles’ energy consumption and, at the same time, help to formulate evolving concepts of smart grid and EV integration.

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