Charging Demand Forecasting is a predictive modeling technique that estimates the temporal and spatial distribution of electric vehicle charging needs within a power system or transportation network to support infrastructure planning and grid integration.
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651
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2017–2026
472
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632
1–5 of 632
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2.1K
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8
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7
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6
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651
Tsinghua University
Beijing, China
19 h-index
63 publications
4.5K citations
North China Electric Power University
Beijing, China
16 h-index
60 publications
5.3K citations
Southeast University
Nanjing, China
16 h-index
71 publications
3.4K citations
Beijing Jiaotong University
Beijing, China
12 h-index
24 publications
1.2K citations
Technical University of Denmark
Kongens Lyngby, Denmark
12 h-index
46 publications
2.1K citations
University of California, Berkeley
Berkeley, United States
11 h-index
22 publications
1.5K citations
Hong Kong Polytechnic University
Hong Kong, Hong Kong
11 h-index
24 publications
1.6K citations
Nanyang Technological University
Singapore, Singapore
10 h-index
27 publications
2.5K citations
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41 publications · 3.9K citations
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28 publications · 1.5K citations
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32 publications · 1.5K citations
22
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- IEEE Transactions on Smart Grid
20 publications · 2.4K citations
20
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- Transportation Research Part D Transport and Environment
21 publications · 1.8K citations
19
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