Forecasting demand for green vehicles
This study presents a model developed based on charging characteristics for different types of Electric Vehicles (EV) such as charging power, nominal range, charging time, State of Charge (SOC) at arrival and departure of electric vehicles, and other influencing factors measurement. In the proposed...
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| Published in: | International Conference on Green Energy, Computing and Intelligent Technology (GEn-CITy 2023) Vol. 2023; pp. 312 - 316 |
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| Main Authors: | , , , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
The Institution of Engineering and Technology
2023
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| Online Access: | Get full text |
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| Summary: | This study presents a model developed based on charging characteristics for different types of Electric Vehicles (EV) such as charging power, nominal range, charging time, State of Charge (SOC) at arrival and departure of electric vehicles, and other influencing factors measurement. In the proposed model, the load profile is forecasted to study the impact of large-scale access of electric vehicles to the grid. This is because when a large-scale electric vehicle is connected to the grid, its charging behaviour will impact the grid. In this study, the Monte Carlo simulation approach will be used to model this in MATLAB and JavaScript. Then, based on the load predicting results of each green vehicle type, implement superposition to produce the total charging load curve and complete the green vehicle charging load forecast. The simulation results show that the proposed model manages to calculate the daily charging load of green vehicles, 2.7 GW to 2.75 GW as well as to determine electric vehicle charging load forecasts. The influence of large-scale electric vehicles connected to the grid is studied using the load forecasting results of green vehicles. |
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| DOI: | 10.1049/icp.2023.1797 |