W. Kanchanachat, I. Masiri, S. Pattarapanitchai, R. Wattan, K. Tohsing, S. Janjai
{"title":"利用地球静止卫星数据计算所有天空条件下相对天空辐射的模型","authors":"W. Kanchanachat, I. Masiri, S. Pattarapanitchai, R. Wattan, K. Tohsing, S. Janjai","doi":"10.1016/j.renene.2025.123423","DOIUrl":null,"url":null,"abstract":"<div><div>Sky radiance data is essential for accurately understanding the distribution of solar radiation over the sky, which is critical for optimizing energy efficiency and system design of solar energy applications. In this study, a model for calculating relative sky radiance under different sky and climate conditions in the tropical environment of Thailand using geostationary satellite data is presented. Five years of measured average sky radiance from a sky scanner at Nakhon Pathom station and cloud index derived from satellite data were used to determine the empirical adjustable coefficients of the proposed model. To validate its performance, relative sky radiance measured at four main regions were analyzed. The results demonstrate that the proposed model performs best under clear sky, with accuracy decreasing under overcast and intermediate sky conditions. The proposed model tends to overestimate relative sky radiance under clear sky and underestimate it under intermediate and overcast sky conditions. However, these discrepancies correspond to findings from previous studies. Furthermore, comparisons with existing models were analyzed, including the CIE standard sky, Igawa, and CIE-NASR models. The comparison revealed that the proposed model mostly obtained higher accuracy than existing models under different sky conditions.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123423"},"PeriodicalIF":9.0000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A model for calculating relative sky radiance under all sky conditions using geostationary satellite data\",\"authors\":\"W. Kanchanachat, I. Masiri, S. Pattarapanitchai, R. Wattan, K. Tohsing, S. Janjai\",\"doi\":\"10.1016/j.renene.2025.123423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Sky radiance data is essential for accurately understanding the distribution of solar radiation over the sky, which is critical for optimizing energy efficiency and system design of solar energy applications. In this study, a model for calculating relative sky radiance under different sky and climate conditions in the tropical environment of Thailand using geostationary satellite data is presented. Five years of measured average sky radiance from a sky scanner at Nakhon Pathom station and cloud index derived from satellite data were used to determine the empirical adjustable coefficients of the proposed model. To validate its performance, relative sky radiance measured at four main regions were analyzed. The results demonstrate that the proposed model performs best under clear sky, with accuracy decreasing under overcast and intermediate sky conditions. The proposed model tends to overestimate relative sky radiance under clear sky and underestimate it under intermediate and overcast sky conditions. However, these discrepancies correspond to findings from previous studies. Furthermore, comparisons with existing models were analyzed, including the CIE standard sky, Igawa, and CIE-NASR models. The comparison revealed that the proposed model mostly obtained higher accuracy than existing models under different sky conditions.</div></div>\",\"PeriodicalId\":419,\"journal\":{\"name\":\"Renewable Energy\",\"volume\":\"251 \",\"pages\":\"Article 123423\"},\"PeriodicalIF\":9.0000,\"publicationDate\":\"2025-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Renewable Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0960148125010857\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960148125010857","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
A model for calculating relative sky radiance under all sky conditions using geostationary satellite data
Sky radiance data is essential for accurately understanding the distribution of solar radiation over the sky, which is critical for optimizing energy efficiency and system design of solar energy applications. In this study, a model for calculating relative sky radiance under different sky and climate conditions in the tropical environment of Thailand using geostationary satellite data is presented. Five years of measured average sky radiance from a sky scanner at Nakhon Pathom station and cloud index derived from satellite data were used to determine the empirical adjustable coefficients of the proposed model. To validate its performance, relative sky radiance measured at four main regions were analyzed. The results demonstrate that the proposed model performs best under clear sky, with accuracy decreasing under overcast and intermediate sky conditions. The proposed model tends to overestimate relative sky radiance under clear sky and underestimate it under intermediate and overcast sky conditions. However, these discrepancies correspond to findings from previous studies. Furthermore, comparisons with existing models were analyzed, including the CIE standard sky, Igawa, and CIE-NASR models. The comparison revealed that the proposed model mostly obtained higher accuracy than existing models under different sky conditions.
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