Cloud Optical Depth Retrievalvia Sky’s Infrared Image for Solar Radiation Prediction

Lai Kok Yee; Tan Lit Ken; Yutaka Asako; Lee Kee Quen; Chuan Zun Liang; Wan Nur Syahidah; Koji Homma; Gerald Pacaba Arada; Gan Yee Siang; Tey Wah Yen; Calvin Kong Leng Sing; Jane Oktavia Kamadinata; Akira Taguchi

Authors

Lai Kok Yee Malaysia –Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (Jalan Semarak), 54100 Kuala Lumpur, Malaysia
Tan Lit Ken Malaysia – Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (Jalan Semarak), 54100 Kuala Lumpur, Malaysia
Yutaka Asako Malaysia –Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (JalanSemarak), 54100 Kuala Lumpur, Malaysia
Lee Kee Quen Malaysia –Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (JalanSemarak), 54100 Kuala Lumpur, Malaysia
Chuan Zun Liang Faculty of Industrial Sciences & Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang, Malaysia
Wan Nur Syahidah Faculty of Industrial Sciences & Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang, Malaysia
Koji Homma International Center, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya-ku, Tokyo, 158-8557, Japan
Gerald Pacaba Arada Electronics and Communications Engineering Department, Gokongwei College of Engineering, De La Salle University, Taft Avenue, Manila, Philippines
Gan Yee Siang Research Center for Healthcare Industry Innovation, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
Tey Wah Yen Malaysia –Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (JalanSemarak), 54100 Kuala Lumpur, Malaysia
Calvin Kong Leng Sing Malaysia – Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (JalanSemarak), 54100 Kuala Lumpur, Malaysia
Jane Oktavia Kamadinata Malaysia – Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra (JalanSemarak), 54100 Kuala Lumpur, Malaysia
Akira Taguchi Department of Computer Science, Faculty of Knowledge Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya-ku, Tokyo, 158-8557, Japan

Keywords:

cloud optical depth, infrared image, solar radiation prediction, artificial neural network

Abstract

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.