PDF
Full
Outline
To improve the prediction accuracy of electric vehicle charging load, a multi time scale prediction model for electric vehicle charging load was designed based on the Lightweight Gradient Boosting Machine (LightGBM) algorithm and travel chain theory. The travel chain was used to describe the user’s travel process, Monte Carlo method was used to extract the spatiotemporal data, and the probability density functions of travel and stay time in different regions was calculated. Newton method was used to divide the probability of charging at multiple time scales, clarifying the spatiotemporal distribution of driving and charging conditions. Fuzzy mathematics theorem and LightGBM were applied to classify charging load data, and a multi season and multi time prediction model were constructed. The efficient parallel computing mode of LightGBM was applied which clarified the variation pattern of charging load, and multi time scale prediction was achieved. The experimental results show that the established model has a prediction error of less than 100 kW and a prediction false alarm rate of less than 3% under different seasons and the number of electric vehicles, and can accurately display the variation pattern of charging load.
PDF
252
105
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
