Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure
The adaptation of modeled solar radiation data with coincident ground measurements has become a standard practice of the industry, typically requested by financial institutions in the detailed solar resource assessments of solar projects. This practice mitigates the risk of solar projects, enhancing...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/13/2127 |
| _version_ | 1797563429171494912 |
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| author | Carlos M. Fernández-Peruchena Jesús Polo Luis Martín Luis Mazorra |
| author_facet | Carlos M. Fernández-Peruchena Jesús Polo Luis Martín Luis Mazorra |
| author_sort | Carlos M. Fernández-Peruchena |
| collection | DOAJ |
| description | The adaptation of modeled solar radiation data with coincident ground measurements has become a standard practice of the industry, typically requested by financial institutions in the detailed solar resource assessments of solar projects. This practice mitigates the risk of solar projects, enhancing the adequate solar plant design and reducing the uncertainty of its yield estimates. This work presents a procedure for improving the accuracy of modeled solar irradiance series through site-adaptation with coincident ground-based measurements relying on the use of a regression preprocessing followed by an empirical quantile mapping (eQM) correction. It was tested at nine sites in a wide range of latitudes and climates, resulting in significant improvements of statistical indicators of dispersion, distribution similarity and overall performance: relative bias is reduced on average from −1.8% and −2.3% to 0.1% and 0.3% for GHI and DNI, respectively; relative root mean square deviation is reduced on average from 17.9% and 34.9% to 14.6% and 29.8% for GHI and DNI, respectively; the distribution similarity is also improved after the site-adaptation (<i>KSI</i> is 3.5 and 3.9 times lower for GHI and DNI at hourly scale, respectively). The methodology is freely available as supplementary material and downloadable as R-package from SiteAdapt. |
| first_indexed | 2024-03-10T18:43:32Z |
| format | Article |
| id | doaj.art-5e3011ac03d240309f4c2ce7846003ed |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T18:43:32Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-5e3011ac03d240309f4c2ce7846003ed2023-11-20T05:41:30ZengMDPI AGRemote Sensing2072-42922020-07-011213212710.3390/rs12132127Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt ProcedureCarlos M. Fernández-Peruchena0Jesús Polo1Luis Martín2Luis Mazorra3National Renewable Energy Centre (CENER), C/Isaac Newton n 4, 41092 Sevilla, SpainPhotovoltaic Solar Energy Unit (Energy Department, CIEMAT), Avda. Complutense 40, 28040 Madrid, SpainQatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha 34110, QatarUniversity Institute for Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Edificio Central del Parque Tecnológico, 35017 Las Palmas de Gran Canaria, SpainThe adaptation of modeled solar radiation data with coincident ground measurements has become a standard practice of the industry, typically requested by financial institutions in the detailed solar resource assessments of solar projects. This practice mitigates the risk of solar projects, enhancing the adequate solar plant design and reducing the uncertainty of its yield estimates. This work presents a procedure for improving the accuracy of modeled solar irradiance series through site-adaptation with coincident ground-based measurements relying on the use of a regression preprocessing followed by an empirical quantile mapping (eQM) correction. It was tested at nine sites in a wide range of latitudes and climates, resulting in significant improvements of statistical indicators of dispersion, distribution similarity and overall performance: relative bias is reduced on average from −1.8% and −2.3% to 0.1% and 0.3% for GHI and DNI, respectively; relative root mean square deviation is reduced on average from 17.9% and 34.9% to 14.6% and 29.8% for GHI and DNI, respectively; the distribution similarity is also improved after the site-adaptation (<i>KSI</i> is 3.5 and 3.9 times lower for GHI and DNI at hourly scale, respectively). The methodology is freely available as supplementary material and downloadable as R-package from SiteAdapt.https://www.mdpi.com/2072-4292/12/13/2127site-adaptationdata fusionbankability of solar projectssatellite-derived irradiancebias removal |
| spellingShingle | Carlos M. Fernández-Peruchena Jesús Polo Luis Martín Luis Mazorra Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure Remote Sensing site-adaptation data fusion bankability of solar projects satellite-derived irradiance bias removal |
| title | Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure |
| title_full | Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure |
| title_fullStr | Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure |
| title_full_unstemmed | Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure |
| title_short | Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure |
| title_sort | site adaptation of modeled solar radiation data the siteadapt procedure |
| topic | site-adaptation data fusion bankability of solar projects satellite-derived irradiance bias removal |
| url | https://www.mdpi.com/2072-4292/12/13/2127 |
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