Can Wan
Impact in
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- Energy Load and Power Forecasting
- Smart Grid Energy Management
- Electric Power System Optimization
- Optimal Power Flow Distribution
- Integrated Energy Systems Optimization
- Electric Vehicles and Infrastructure
Papers in
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- Energy Load and Power Forecasting 40
- Smart Grid Energy Management 38
- Electric Power System Optimization 34
- Optimal Power Flow Distribution 33
- Integrated Energy Systems Optimization 11
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- Microgrid Control and Optimization 24
- Co-authors
- Yonghua Song (51 shared papers)Zhao Xu (20 shared papers)Zhao Yang Dong (12 shared papers)Kit Po Wong (8 shared papers)Pierre Pinson (3 shared papers)Jin Lin (15 shared papers)Jianhui Wang (6 shared papers)Changfei Zhao (10 shared papers)
In The Last Decade
Can Wan
100 papers receiving 4.3k citations
Can Wan's Hit Papers
Peers
Comparison fields: 5 of 97
- Energy Engineering and Power Technology 363
- Electrical and Electronic Engineering 3.8k
- Control and Systems Engineering 1.2k
- Safety, Risk, Reliability and Quality 257
- Artificial Intelligence 858
Countries citing papers authored by Can Wan
This map shows the geographic impact of Can Wan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Can Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Wan more than expected).
Fields of papers citing papers by Can Wan
This network shows the impact of papers produced by Can Wan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Can Wan. The network helps show where Can Wan may publish in the future.
Co-authors
The 25 scholars most cited alongside Can Wan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine Hit paper breakdown → | 2013 | 606 |
| 2 | 2014 | 276 | |
| 3 | 2016 | 233 | |
| 4 | 2013 | 186 | |
| 5 | 2016 | 140 | |
| 6 | 2018 | 131 | |
| 7 | 2018 | 121 | |
| 8 | 2013 | 113 | |
| 9 | 2015 | 103 | |
| 10 | 2017 | 99 | |
| 11 | 2019 | 96 | |
| 12 | 2013 | 95 | |
| 13 | 2016 | 93 | |
| 14 | 2012 | 93 | |
| 15 | 2014 | 86 | |
| 16 | 2018 | 84 | |
| 17 | 2019 | 78 | |
| 18 | 2016 | 73 | |
| 19 | 2018 | 72 | |
| 20 | 2021 | 70 |
About Can Wan
Can Wan is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering, Artificial Intelligence, Safety, Risk, Reliability and Quality and Management Science and Operations Research, having authored 111 papers that have together received 4.4k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (40 papers), Smart Grid Energy Management (38 papers), Electric Power System Optimization (34 papers), Optimal Power Flow Distribution (33 papers), Microgrid Control and Optimization (24 papers), Machine Learning and ELM (13 papers), Power System Reliability and Maintenance (11 papers) and Integrated Energy Systems Optimization (11 papers). The work is most often cited by research in Energy Engineering and Power Technology (363 citations), Electrical and Electronic Engineering (3.8k citations), Control and Systems Engineering (1.2k citations), Safety, Risk, Reliability and Quality (257 citations) and Artificial Intelligence (858 citations). Can Wan has collaborated with scholars based in China, Macao and Hong Kong. Frequent co-authors include Yonghua Song, Zhao Xu, Zhao Yang Dong, Kit Po Wong, Pierre Pinson, Jin Lin, Jianhui Wang, Changfei Zhao, Erbao Cao and Yibao Jiang. Their work appears in journals such as IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, Journal of Modern Power Systems and Clean Energy and IET Generation Transmission & Distribution.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.