Oumaima Kanibou, Omkaltoume El Fatni, A. Maftouh, El Houssaine El Rhaleb, M. Bargach
{"title":"用于优化主动式日光照明系统的直接正常辐照比较","authors":"Oumaima Kanibou, Omkaltoume El Fatni, A. Maftouh, El Houssaine El Rhaleb, M. Bargach","doi":"10.4028/p-hjdy4u","DOIUrl":null,"url":null,"abstract":"Active daylighting technology, encompassing techniques for utilizing natural light without converting it into heat or electrical energy, proves highly beneficial in sun-rich countries like Morocco. Unlike solar technologies, which capture global radiation, daylighting technology specifically leverages direct sun radiation. This study focuses on three semi-empirical models: Perrin de Brichambaut, Kasten, and Ghouard, utilizing data from the PVGIS website to develop and evaluate these systems. Comparison of experimentally obtained direct normal irradiation results against these models and the PVGIS website identifies the Kasten model as the most suitable choice, supported by the high R2 values of 0.9954, 0.9933, 0.9951, and 0.9906 for winter, spring, summer, and autumn, respectively. Furthermore, the model exhibits a minimum Mean Absolute Error (MAE) of 12.34, 24.29, 25.93, and 29.51 W/m², an optimal Mean Squared Error (MSE) of 238.16, 1129.5, 1039.9, and 1520.7 W²/m⁴, and a variance of 216.40, 1099.3, 1015.4, and 1460 for the respective seasons. These results strongly indicate the Kasten model's suitability for the climatic conditions of the studied site in Morocco, showcasing high correlation coefficients and low prediction errors. The findings underscore the Kasten model as the most fitting choice for optimizing active daylighting technology in Morocco's climate.","PeriodicalId":507603,"journal":{"name":"International Journal of Engineering Research in Africa","volume":"17 15","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparisons of Direct Normal Irradiation for the Optimization of Active Daylighting Systems\",\"authors\":\"Oumaima Kanibou, Omkaltoume El Fatni, A. Maftouh, El Houssaine El Rhaleb, M. Bargach\",\"doi\":\"10.4028/p-hjdy4u\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Active daylighting technology, encompassing techniques for utilizing natural light without converting it into heat or electrical energy, proves highly beneficial in sun-rich countries like Morocco. Unlike solar technologies, which capture global radiation, daylighting technology specifically leverages direct sun radiation. This study focuses on three semi-empirical models: Perrin de Brichambaut, Kasten, and Ghouard, utilizing data from the PVGIS website to develop and evaluate these systems. Comparison of experimentally obtained direct normal irradiation results against these models and the PVGIS website identifies the Kasten model as the most suitable choice, supported by the high R2 values of 0.9954, 0.9933, 0.9951, and 0.9906 for winter, spring, summer, and autumn, respectively. Furthermore, the model exhibits a minimum Mean Absolute Error (MAE) of 12.34, 24.29, 25.93, and 29.51 W/m², an optimal Mean Squared Error (MSE) of 238.16, 1129.5, 1039.9, and 1520.7 W²/m⁴, and a variance of 216.40, 1099.3, 1015.4, and 1460 for the respective seasons. These results strongly indicate the Kasten model's suitability for the climatic conditions of the studied site in Morocco, showcasing high correlation coefficients and low prediction errors. The findings underscore the Kasten model as the most fitting choice for optimizing active daylighting technology in Morocco's climate.\",\"PeriodicalId\":507603,\"journal\":{\"name\":\"International Journal of Engineering Research in Africa\",\"volume\":\"17 15\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering Research in Africa\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4028/p-hjdy4u\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering Research in Africa","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/p-hjdy4u","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparisons of Direct Normal Irradiation for the Optimization of Active Daylighting Systems
Active daylighting technology, encompassing techniques for utilizing natural light without converting it into heat or electrical energy, proves highly beneficial in sun-rich countries like Morocco. Unlike solar technologies, which capture global radiation, daylighting technology specifically leverages direct sun radiation. This study focuses on three semi-empirical models: Perrin de Brichambaut, Kasten, and Ghouard, utilizing data from the PVGIS website to develop and evaluate these systems. Comparison of experimentally obtained direct normal irradiation results against these models and the PVGIS website identifies the Kasten model as the most suitable choice, supported by the high R2 values of 0.9954, 0.9933, 0.9951, and 0.9906 for winter, spring, summer, and autumn, respectively. Furthermore, the model exhibits a minimum Mean Absolute Error (MAE) of 12.34, 24.29, 25.93, and 29.51 W/m², an optimal Mean Squared Error (MSE) of 238.16, 1129.5, 1039.9, and 1520.7 W²/m⁴, and a variance of 216.40, 1099.3, 1015.4, and 1460 for the respective seasons. These results strongly indicate the Kasten model's suitability for the climatic conditions of the studied site in Morocco, showcasing high correlation coefficients and low prediction errors. The findings underscore the Kasten model as the most fitting choice for optimizing active daylighting technology in Morocco's climate.