E3S Web Conf.
Volume 194, 20202020 5th International Conference on Advances in Energy and Environment Research (ICAEER 2020)
|Number of page(s)||4|
|Section||Renewable Energy and New Energy Technology|
|Published online||15 October 2020|
Forecasting method of electric vehicle load time-space distribution considering traffic distribution
1 Marketing Service Center of State Grid Tianjin Electric Power Company, Tianjin, 300202, China
2 State Grid Tianjin Electric Power Company, Tianjin, 300010, China
3 China Electric Power Research Institute, Beijing, 100192, China
* Corresponding author's e-mail: email@example.com
The main work of this paper is to establish an electric vehicle(EV) load forecasting model based on road network traffic distribution for urban and inter-city transportation networks. This paper established a road network model considering the traffic impedance for the EV load forecasting of the urban fast charging network, and studied the prediction method of the time-space distribution of EV charging demand in the fast charging mode .Based on the expressway, the method for predicting the time-space distribution of EV load in the inter-city fast charging network is studied, and a time-space distribution load forecasting model is established. Based on the time-space distribution of traffic flow, combined with EV charging characteristics and travel routes, load simulation is performed. By constructing a prediction method for the time-space distribution of EV charging demand in the fast charging mode, it provides theoretical and methodological support for the research of time-sharing and segmented metering and charging strategies for EV fast charging stations,, and provides an important reference for the development of EV charging facilities operating cost benefits, economic performance indicators and calculation models under fast charging mode, which are of great significance to promote the popularization and application of EV fast charging modes.
© The Authors, published by EDP Sciences, 2020
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