Simulation and Correction Study of Solar Irradiance in Guangdong Based on WRF-Solar and Random Forest.
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| Title: | Simulation and Correction Study of Solar Irradiance in Guangdong Based on WRF-Solar and Random Forest. |
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| Authors: | He, Yuanhong1 (AUTHOR), Li, Zheng1 (AUTHOR), Zhou, Fang1 (AUTHOR), Gao, Zhiqiu1 (AUTHOR) zgao@nuist.edu.cn |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 9, p2077. 18p. |
| Subject Terms: | *Random forest algorithms, *Calibration, *Energy industry forecasting, *Numerical weather forecasting, *Solar radiation |
| Geographic Terms: | China, Guangdong Sheng (China) |
| Abstract: | To improve solar irradiance simulation accuracy for precise photovoltaic power forecasting, we developed a hybrid framework combining WRF-Solar numerical simulation and random forest (RF) machine learning for a PV plant in Guangdong, China. Weather conditions were objectively classified into clear, intermittent cloudy, and overcast using the Daily Variability Index (DVI) and Daily Clear-sky Index (DCI). We calibrated the WRF-Solar model's microphysics and radiative transfer schemes via sensitivity tests to optimize overcast-sky performance, then applied RF correction to the simulated irradiance. Results show that RF correction significantly reduces simulation errors for intermittent and overcast conditions, while the original WRF-Solar outperforms the corrected results under clear skies due to RF overfitting. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 193715973 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Simulation and Correction Study of Solar Irradiance in Guangdong Based on WRF-Solar and Random Forest. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22He%2C+Yuanhong%22">He, Yuanhong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zheng%22">Li, Zheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Fang%22">Zhou, Fang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gao%2C+Zhiqiu%22">Gao, Zhiqiu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zgao@nuist.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 9, p2077. 18p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Random+forest+algorithms%22">Random forest algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Calibration%22">Calibration</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+industry+forecasting%22">Energy industry forecasting</searchLink><br />*<searchLink fieldCode="DE" term="%22Numerical+weather+forecasting%22">Numerical weather forecasting</searchLink><br />*<searchLink fieldCode="DE" term="%22Solar+radiation%22">Solar radiation</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink><br /><searchLink fieldCode="DE" term="%22Guangdong+Sheng+%28China%29%22">Guangdong Sheng (China)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: To improve solar irradiance simulation accuracy for precise photovoltaic power forecasting, we developed a hybrid framework combining WRF-Solar numerical simulation and random forest (RF) machine learning for a PV plant in Guangdong, China. Weather conditions were objectively classified into clear, intermittent cloudy, and overcast using the Daily Variability Index (DVI) and Daily Clear-sky Index (DCI). We calibrated the WRF-Solar model's microphysics and radiative transfer schemes via sensitivity tests to optimize overcast-sky performance, then applied RF correction to the simulated irradiance. Results show that RF correction significantly reduces simulation errors for intermittent and overcast conditions, while the original WRF-Solar outperforms the corrected results under clear skies due to RF overfitting. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193715973 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19092077 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 2077 Subjects: – SubjectFull: Random forest algorithms Type: general – SubjectFull: Calibration Type: general – SubjectFull: Energy industry forecasting Type: general – SubjectFull: Numerical weather forecasting Type: general – SubjectFull: Solar radiation Type: general – SubjectFull: China Type: general – SubjectFull: Guangdong Sheng (China) Type: general Titles: – TitleFull: Simulation and Correction Study of Solar Irradiance in Guangdong Based on WRF-Solar and Random Forest. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: He, Yuanhong – PersonEntity: Name: NameFull: Li, Zheng – PersonEntity: Name: NameFull: Zhou, Fang – PersonEntity: Name: NameFull: Gao, Zhiqiu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 9 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
