Tan, Lit Ken and Ong, Sie Meng and Nor Azwadi, Che Sidik and Asako, Yutaka and Lee, Kee Quen and Gan, Yee Siang and Goh, Chien Yong and Tey, Wah Yen and Ngien, S. K. and Chuan, Zun Liang (2017) Forecasting Multivariate Time Series Meteorological Data for Solar Thermal Cogeneration Systems. In: Seoul International Conference on Applied Science and Engineering , 5-7 December 2017 , Seoul, Korea. pp. 69-83. (SICASE-0002). ISBN 978-986-89536-5-9
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Abstract
The high usage of fossil fuel to produce energy for the increasing demand of energy has been the primary culprit behind global warming. Alternative energy supply is thus necessary in order to prevent the situation from worsening. Recently, renewable energies such as solar energy has emerged as potential alternative energy resources due to its abundance all over the globe Solar energy can be harnessed using available system such as solar thermal cogeneration systems. However, fluctuations of solar radiation is one of the main challenge faced by the implementation of solar thermal cogeneration system due to its high variability. In order to have solar thermal cogeneration systems function smoothly and continuously, knowledge on solar radiation’s intensity several minutes in advance are required. While there exist various solar radiation forecast models, most of the proposed model are time consuming. In this research, a new methodology to forecast solar radiation via several meteorological data that incorporates dimension reduction technique is proposed. Based on the proposed methodology, two prediction models, Artificial Neural Network and statistical are established.
| Item Type: | Conference or Workshop Item (Lecture) |
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| Uncontrolled Keywords: | Solar radiation, Forecast, Artificial Neural Network, Time series |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
| Faculty/Division: | Centre of Excellence: Centre for Earth Resources Research & Management Faculty of Civil Engineering & Earth Resources |
| Depositing User: | Dr Su Kong Ngien |
| Date Deposited: | 09 Jan 2018 07:39 |
| Last Modified: | 18 Jul 2018 08:25 |
| URI: | http://umpir.ump.edu.my/id/eprint/19837 |
| Download Statistic: | View Download Statistics |
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