%0 Conference Paper
%A Assadi, M.K.
%A Bin Abdul Razak, A.F.Q.
%A Habib, K.
%D 2014
%F scholars:5082
%I EDP Sciences
%K Neural networks, Annual average; Artificial networks; Artificial neural network modeling; Clearness indices; Horizontal surfaces; Limited data; Solar energy applications; Solar research, Solar energy
%R 10.1051/matecconf/20141302015
%T Solar energy potential estimation in perak using clearness index and artificial neural network
%U https://khub.utp.edu.my/scholars/5082/
%V 13
%X In this paper solar energy potential has been estimated by two methods which are clearness index and artificial network (ANN) methods. The selected region is Seri Iskandar, Perak (4°24�latitude, 100°58�E longitude, 24 m altitude). Experimental data (monthly average daily radiation on horizontal surface) was obtained from UTP solar research site in UTP campus. The data include the period of 2010 to 2012 and were used for testing the artificial neural network model and also for determination of clearness index. Also the experimental data of the three meteorological, Ipoh, Bayan Lepas & KLIA were used in calculating the clearness index and for training the neural network. Result shows that clearness index for Seri Iskandar is 0.52, the highest radiation is on February (20.45 MJ/m2/day), annual average is 18.25 MJ/m2/day and clearness index is more accurate than ANN when there is limited data supply. In general, Perak states show strong potential for solar energy application. © 2014 Owned by the authors, published by EDP Sciences.
%Z cited By 2; Conference of 4th International Conference on Production, Energy and Reliability, ICPER 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:106620