Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction
Photovoltaic (PV) system is developed to harness solar energy as an alternative energy to reduce the dependency on fossil fuel energy. However, the output of the PV system is not stable due to the fluctuation of solar radiation. Hence, solar radiation prediction in advanced is needed to make sure th...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Akademi Baru
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/30412/ http://umpir.ump.edu.my/id/eprint/30412/1/Cloud%20optical%20depth%20retrieval%20via%20sky%E2%80%99s%20infrared%20image.pdf |
| _version_ | 1848823507257917440 |
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| author | Lai, Kok Yee Tan, Lit Ken Asako, Yutaka Lee, Kee Quen Chuan, Zun Liang Wan Nur Syahidah, Wan Yusoff Homma, Koji Arada, Gerald Pacaba Gan, Yee Siang Tey, Wah Yen Kong, Calvin Leng Sing Kamadinata, Jane Oktavia Taguchi, Akira |
| author_facet | Lai, Kok Yee Tan, Lit Ken Asako, Yutaka Lee, Kee Quen Chuan, Zun Liang Wan Nur Syahidah, Wan Yusoff Homma, Koji Arada, Gerald Pacaba Gan, Yee Siang Tey, Wah Yen Kong, Calvin Leng Sing Kamadinata, Jane Oktavia Taguchi, Akira |
| author_sort | Lai, Kok Yee |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Photovoltaic (PV) system is developed to harness solar energy as an alternative energy to reduce the dependency on fossil fuel energy. However, the output of the PV system is not stable due to the fluctuation of solar radiation. Hence, solar radiation prediction in advanced is needed to make sure the tap changer in PV system has enough time to respond. In this research, the cloud base temperature is identified from the sky’s thermal image. From the cloud base temperature, cloud optical depth (COD) is calculated. Artificial neural network (ANN) models are established by using different combinations of current solar radiation and COD to predict the solar radiation several minutes in advanced. R-squared value is used to measure the accuracy of the models. For prediction in advanced for every minute, with COD as input, always show the highest R-squared value. The highest R-squared value is 0.8899 for the prediction for 1 minute in advanced and dropped to 0.5415 as the minute of prediction in advanced increase to 5. This shows that the proposed methodology is suitable for prediction of solar radiation for short term in advanced. |
| first_indexed | 2025-11-15T02:58:14Z |
| format | Article |
| id | ump-30412 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:58:14Z |
| publishDate | 2019 |
| publisher | Akademi Baru |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-304122022-01-18T02:04:20Z http://umpir.ump.edu.my/id/eprint/30412/ Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction Lai, Kok Yee Tan, Lit Ken Asako, Yutaka Lee, Kee Quen Chuan, Zun Liang Wan Nur Syahidah, Wan Yusoff Homma, Koji Arada, Gerald Pacaba Gan, Yee Siang Tey, Wah Yen Kong, Calvin Leng Sing Kamadinata, Jane Oktavia Taguchi, Akira TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Photovoltaic (PV) system is developed to harness solar energy as an alternative energy to reduce the dependency on fossil fuel energy. However, the output of the PV system is not stable due to the fluctuation of solar radiation. Hence, solar radiation prediction in advanced is needed to make sure the tap changer in PV system has enough time to respond. In this research, the cloud base temperature is identified from the sky’s thermal image. From the cloud base temperature, cloud optical depth (COD) is calculated. Artificial neural network (ANN) models are established by using different combinations of current solar radiation and COD to predict the solar radiation several minutes in advanced. R-squared value is used to measure the accuracy of the models. For prediction in advanced for every minute, with COD as input, always show the highest R-squared value. The highest R-squared value is 0.8899 for the prediction for 1 minute in advanced and dropped to 0.5415 as the minute of prediction in advanced increase to 5. This shows that the proposed methodology is suitable for prediction of solar radiation for short term in advanced. Akademi Baru 2019-06-01 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/30412/1/Cloud%20optical%20depth%20retrieval%20via%20sky%E2%80%99s%20infrared%20image.pdf Lai, Kok Yee and Tan, Lit Ken and Asako, Yutaka and Lee, Kee Quen and Chuan, Zun Liang and Wan Nur Syahidah, Wan Yusoff and Homma, Koji and Arada, Gerald Pacaba and Gan, Yee Siang and Tey, Wah Yen and Kong, Calvin Leng Sing and Kamadinata, Jane Oktavia and Taguchi, Akira (2019) Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 58 (1). pp. 1-14. ISSN 2289-7879. (Published) http://www.akademiabaru.com/submit/index.php/arfmts/article/view/2560 |
| spellingShingle | TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Lai, Kok Yee Tan, Lit Ken Asako, Yutaka Lee, Kee Quen Chuan, Zun Liang Wan Nur Syahidah, Wan Yusoff Homma, Koji Arada, Gerald Pacaba Gan, Yee Siang Tey, Wah Yen Kong, Calvin Leng Sing Kamadinata, Jane Oktavia Taguchi, Akira Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| title | Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| title_full | Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| title_fullStr | Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| title_full_unstemmed | Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| title_short | Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| title_sort | cloud optical depth retrieval via sky’s infrared image for solar radiation prediction |
| topic | TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/30412/ http://umpir.ump.edu.my/id/eprint/30412/ http://umpir.ump.edu.my/id/eprint/30412/1/Cloud%20optical%20depth%20retrieval%20via%20sky%E2%80%99s%20infrared%20image.pdf |