The DOI matches its Crossref record; 30 of the 31 references it cites were found in a registry or an index.
Machine learning for solar irradiance forecasting of photovoltaic system
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“To date, many ML methods have been used to forecast electricity supply and demand.”
From Tackling climate change with machine learning (2023) · cites this paper as [478]
Citations
Cites
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Self-citation
Research works printed but not linked: 2
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Cited by
Sorted by citations
Zendehboudi, A., Baseer, M. A., & Saidur, R. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.07.164 · Cited by 635
Yang, D., Kleissl, J. P., Gueymard, C. A., Pedro, H. T. C., & Coimbra, C. F. M. (2018) · Solar Energy · doi:10.1016/j.solener.2017.11.023 · Cited by 584
Hossain, E., Khan, I., Un-Noor, F., Sikander, S. S., & Sunny, M. S. H. (2019) · IEEE Access · doi:10.1109/access.2019.2894819 · Cited by 536
Deep learning models for solar irradiance forecasting: A comprehensive review
Kumari, P., & Toshniwal, D. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.128566 · Cited by 463
Benti, N. E., Chaka, M. D., & Semie, A. G. (2023) · Sustainability · doi:10.3390/su15097087 · Cited by 470
Metadata
- Authors
- Li, J., Ward, J. K., Tong, J., Collins, L., & Platt, G.
- Affiliations
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Corresponding author
- Li, Jiaming
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2016-05
- Volume
- 90
- Pages
- 542-553
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W2287933588
- Cited by
- 186
- References
- 31
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 28 · 2023: 27 · 2022: 24 · 2021: 25 · 2020: 13 · 2019: 12 · 2018: 14 · 2017: 10 · 2016: 3
- FWCI
- 10.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Renewable Energy (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Australian Renewable Energy Agency
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Solar Radiation and Photovoltaics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Photovoltaic System Optimization Techniques
- Keywords
- solar irradiance forecasting, photovoltaic systems, short-term forecasting, hidden Markov models, support vector regression, distributed generation, forecast performance comparison
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