Upma Singh
Impact in
-
- Hybrid Renewable Energy Systems
-
- Energy Load and Power Forecasting
- Electric Power System Optimization
- Smart Grid Energy Management
Papers in
-
- Energy Load and Power Forecasting 9
- Electric Power System Optimization 4
-
- Solar Radiation and Photovoltaics 5
- Co-authors
- M. Rizwan (8 shared papers)M. Rizwan (1 shared paper)Ibrahim Alsaidan (1 shared paper)Muhannad Alaraj (1 shared paper)Hasmat Malik (2 shared papers)Fausto Pedro Garcı́a Márquez (1 shared paper)Saket Gupta (1 shared paper)Majed A. Alotaibi (1 shared paper)
- Journals
- Energies (2 papers)Results in Engineering (1 paper)IET Renewable Power Generation (1 paper)Energy Sources Part A Recovery Utilization and Environmental Effects (1 paper)Journal of Ambient Intelligence and Humanized Computing (1 paper)
- Partner nations
- IndiaSaudi ArabiaMalaysia
In The Last Decade
Upma Singh
10 papers receiving 314 citations
Peers
Comparison fields: 5 of 74
- Energy Engineering and Power Technology 26
- Electrical and Electronic Engineering 183
- Pollution 32
- Control and Systems Engineering 55
- Artificial Intelligence 75
Countries citing papers authored by Upma Singh
This map shows the geographic impact of Upma Singh'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 Upma Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Upma Singh more than expected).
Fields of papers citing papers by Upma Singh
This network shows the impact of papers produced by Upma Singh. 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 Upma Singh. The network helps show where Upma Singh may publish in the future.
Co-authors
The 9 scholars most cited alongside Upma Singh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 144 | |
| 2 | 2022 | 58 | |
| 3 | 2022 | 49 | |
| 4 | 2022 | 31 | |
| 5 | 2022 | 14 | |
| 6 | 2025 | 9 | |
| 7 | 2021 | 9 | |
| 8 | 2018 | 7 | |
| 9 | 2022 | 6 | |
| 10 | 2024 | 1 | |
| 11 | 2026 | 0 | |
| 12 | 2012 | 0 | |
| 13 | 2024 | 0 |
About Upma Singh
Upma Singh is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Management Science and Operations Research, Aerospace Engineering and Pollution, having authored 13 papers that have together received 328 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (9 papers), Solar Radiation and Photovoltaics (5 papers), Electric Power System Optimization (4 papers), Wind Energy Research and Development (4 papers), Stock Market Forecasting Methods (3 papers), Photovoltaic System Optimization Techniques (2 papers), Energy and Environment Impacts (2 papers) and Hybrid Renewable Energy Systems (1 paper). The work is most often cited by research in Energy Engineering and Power Technology (26 citations), Electrical and Electronic Engineering (183 citations), Pollution (32 citations), Control and Systems Engineering (55 citations) and Artificial Intelligence (75 citations). Upma Singh has collaborated with scholars based in India, Saudi Arabia and Malaysia. Frequent co-authors include M. Rizwan, M. Rizwan, Ibrahim Alsaidan, Muhannad Alaraj, Hasmat Malik, Fausto Pedro Garcı́a Márquez, Saket Gupta, Majed A. Alotaibi and Sandeep Singh. Their work appears in journals such as Energies, Results in Engineering, IET Renewable Power Generation, Energy Sources Part A Recovery Utilization and Environmental Effects and Journal of Ambient Intelligence and Humanized Computing.
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.