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...
Saved in:
Main Authors: | , , , , , , , , , , , , |
---|---|
Format: | Article |
Published: |
Penerbit Akademia Baru
2019
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/89197/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.89197 |
---|---|
record_format |
eprints |
spelling |
my.utm.891972021-02-09T02:37:32Z http://eprints.utm.my/id/eprint/89197/ Cloud optical depth retrieval via sky's infrared image for solar radiation prediction Yee, L. K. Ken, T. L. Asako, Y. Quen, L. K. Liang, C. Z. Syahidah, W. N. Homma, K. Arada, G. P. Siang, G. Y. Yen, T. W. Sing, C. K. L. Kamadinata, J. O. Taguchi, A. T Technology (General) 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. Penerbit Akademia Baru 2019-06 Article PeerReviewed Yee, L. K. and Ken, T. L. and Asako, Y. and Quen, L. K. and Liang, C. Z. and Syahidah, W. N. and Homma, K. and Arada, G. P. and Siang, G. Y. and Yen, T. W. and Sing, C. K. L. and Kamadinata, J. O. and Taguchi, A. (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 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
topic |
T Technology (General) |
spellingShingle |
T Technology (General) Yee, L. K. Ken, T. L. Asako, Y. Quen, L. K. Liang, C. Z. Syahidah, W. N. Homma, K. Arada, G. P. Siang, G. Y. Yen, T. W. Sing, C. K. L. Kamadinata, J. O. Taguchi, A. Cloud optical depth retrieval via sky's infrared image for solar radiation prediction |
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. |
format |
Article |
author |
Yee, L. K. Ken, T. L. Asako, Y. Quen, L. K. Liang, C. Z. Syahidah, W. N. Homma, K. Arada, G. P. Siang, G. Y. Yen, T. W. Sing, C. K. L. Kamadinata, J. O. Taguchi, A. |
author_facet |
Yee, L. K. Ken, T. L. Asako, Y. Quen, L. K. Liang, C. Z. Syahidah, W. N. Homma, K. Arada, G. P. Siang, G. Y. Yen, T. W. Sing, C. K. L. Kamadinata, J. O. Taguchi, A. |
author_sort |
Yee, L. K. |
title |
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_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_sort |
cloud optical depth retrieval via sky's infrared image for solar radiation prediction |
publisher |
Penerbit Akademia Baru |
publishDate |
2019 |
url |
http://eprints.utm.my/id/eprint/89197/ |
_version_ |
1691733080762482688 |
score |
13.18916 |