Kun Ding

1.4k citations
75 papers · 1.0k · h-index 16

Impact in

Papers in

Kun Ding

65 papers receiving 970 citations

Peers

Kun Ding
Comparison fields: 5 of 70
  • Renewable Energy, Sustainability and the Environment 626
  • Energy Engineering and Power Technology 70
  • Artificial Intelligence 424
  • Electrical and Electronic Engineering 567
  • Control and Systems Engineering 213
Replace Siva Ramakrishna Madeti with:
Siva Ramakrishna Madeti India
Mahmoud Dhimish United Kingdom
Mohammed Ali Khan India
Azhar Ul-Haq Pakistan
Bruce Mehrdadi United Kingdom
Yassine Chaibi Morocco
Kuei‐Hsiang Chao Taiwan
Ainhoa Galarza Spain
Dhanup S. Pillai India
Masoud Ahmadipour Malaysia
Kun Ding relative to Siva Ramakrishna Madeti India Siva Ramakrishna Madeti's profile →
Citations per field
00.5×2×3×4×
Siva Ramakrishna Madeti · 1×
Citations per year

Countries citing papers authored by Kun Ding

Since Specialization
Citations

This map shows the geographic impact of Kun Ding'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 Kun Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Ding more than expected).

Fields of papers citing papers by Kun Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kun Ding. 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 Kun Ding. The network helps show where Kun Ding may publish in the future.

Co-authors

The 25 scholars most cited alongside Kun Ding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kun Ding Line = papers co-authored together Kun Ding links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012236
2 202172
3 201458
4 201856
5 202245
6
Power Characteristics of Jiuquan Wind Power Base
201039
7 202137
8 202236
9 201333
10 202330
11 202325
12 201924
13 202422
14 202318
15 202218
16 201915
17 202315
18 201214
19 201614
20 201814

About Kun Ding

Kun Ding is a scholar working on Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering, Artificial Intelligence, Control and Systems Engineering and Energy Engineering and Power Technology, having authored 75 papers that have together received 1.0k indexed citations. Recurring topics across this work include Photovoltaic System Optimization Techniques (36 papers), Solar Radiation and Photovoltaics (25 papers), Power Systems and Renewable Energy (14 papers), Solar Thermal and Photovoltaic Systems (11 papers), solar cell performance optimization (11 papers), Energy Load and Power Forecasting (7 papers), Microgrid Control and Optimization (5 papers) and Smart Grid and Power Systems (5 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (626 citations), Energy Engineering and Power Technology (70 citations), Artificial Intelligence (424 citations), Electrical and Electronic Engineering (567 citations) and Control and Systems Engineering (213 citations). Kun Ding has collaborated with scholars based in China, Germany and Singapore. Frequent co-authors include Tao Peng, Jingwei Zhang, Jingwei Zhang, Yongjie Liu, Zenan Yang, Xiang Chen, Yuanliang Li, Jun‐Wei Xu, Thomas Reindl and Meng Jiang. Their work appears in journals such as Energy, Energy Conversion and Management, Solar Energy, IET Renewable Power Generation and Energies.

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.

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