Principal Component Analysis on Meteorological Data in UTM KL - Tan, Lit Ken; Ong, Sie Meng; Lee, Kee Quen; Gan, Yee Siang; Goh, Chien Yong; Tey, Wah Yen; Ngien, S. K. (Penerbit Akademia Baru, 2017)
The high usage of fossil fuel to produce energy for the increasing demand of energy has been the primary culprit behind global warming. Renewable energies such as solar energy can be a solution in preventing the situation from worsening. Solar energy can be harnessed using available system such as solar thermal cogeneration systems. However, for the system to function smoothly and continuously, knowledge on solar radiation’s intensity several minutes in advance are required. Though there exist various solar radiation forecast models, most of the existing models requires high computational time. In this research, principal component analysis were applied on the meteorological data collected in Universiti Teknologi Malaysia Kuala Lumpur to reduce the dimension of the data. Dominant factors obtained from the analysis is expected to be useful for the development of solar radiation forecast model.