Hao Quan
Impact in
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- Energy Load and Power Forecasting
- Electric Power System Optimization
- Smart Grid Energy Management
- Optimal Power Flow Distribution
Papers in
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- Energy Load and Power Forecasting 24
- Electric Power System Optimization 14
- Optimal Power Flow Distribution 4
- Electric Vehicles and Infrastructure 4
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- Solar Radiation and Photovoltaics 15
- Co-authors
- Dipti Srinivasan (25 shared papers)Abbas Khosravi (9 shared papers)Wenjie Zhang (15 shared papers)Dazhi Yang (7 shared papers)Ashwin M. Khambadkone (2 shared papers)Carlos D. Rodríguez‐Gallegos (6 shared papers)Oktoviano Gandhi (7 shared papers)Vahid R. Disfani (2 shared papers)
In The Last Decade
Hao Quan
52 papers receiving 1.9k citations
Hao Quan's Hit Papers
Peers
Comparison fields: 5 of 91
- Energy Engineering and Power Technology 99
- Electrical and Electronic Engineering 1.5k
- Management Science and Operations Research 312
- Artificial Intelligence 665
- Renewable Energy, Sustainability and the Environment 209
Countries citing papers authored by Hao Quan
This map shows the geographic impact of Hao Quan'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 Hao Quan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Quan more than expected).
Fields of papers citing papers by Hao Quan
This network shows the impact of papers produced by Hao Quan. 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 Hao Quan. The network helps show where Hao Quan may publish in the future.
Co-authors
The 25 scholars most cited alongside Hao Quan, 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 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals Hit paper breakdown → | 2013 | 507 |
| 2 | 2018 | 176 | |
| 3 | 2015 | 155 | |
| 4 | 2014 | 126 | |
| 5 | 2013 | 110 | |
| 6 | 2019 | 92 | |
| 7 | 2014 | 85 | |
| 8 | 2018 | 84 | |
| 9 | 2020 | 62 | |
| 10 | 2017 | 62 | |
| 11 | 2016 | 56 | |
| 12 | 2017 | 55 | |
| 13 | 2021 | 48 | |
| 14 | 2018 | 42 | |
| 15 | 2023 | 28 | |
| 16 | 2018 | 27 | |
| 17 | 2020 | 26 | |
| 18 | 2012 | 18 | |
| 19 | 2023 | 16 | |
| 20 | 2023 | 15 |
About Hao Quan
Hao Quan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research and Biomedical Engineering, having authored 55 papers that have together received 1.9k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (24 papers), Solar Radiation and Photovoltaics (15 papers), Electric Power System Optimization (14 papers), Microgrid Control and Optimization (7 papers), Power System Reliability and Maintenance (5 papers), Superconducting Materials and Applications (4 papers), Optimal Power Flow Distribution (4 papers) and Electric Vehicles and Infrastructure (4 papers). The work is most often cited by research in Energy Engineering and Power Technology (99 citations), Electrical and Electronic Engineering (1.5k citations), Management Science and Operations Research (312 citations), Artificial Intelligence (665 citations) and Renewable Energy, Sustainability and the Environment (209 citations). Hao Quan has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Dipti Srinivasan, Abbas Khosravi, Wenjie Zhang, Dazhi Yang, Ashwin M. Khambadkone, Carlos D. Rodríguez‐Gallegos, Oktoviano Gandhi, Vahid R. Disfani, Licheng Liu and Chin‐Woo Tan. Their work appears in journals such as Applied Energy, Solar Energy, IEEE Transactions on Applied Superconductivity, IEEE Transactions on Neural Networks and Learning Systems and Energy.
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.