New Technique for Estimating the Monthly Average Daily Global Solar Radiation Using Bees Algorithm and Empirical Equations

被引:13
作者
Tolabi, Hajar Bagheri [1 ]
Ayob, Shahrin Bin Md [2 ]
Moradi, M. H. [3 ]
Shakarmi, Mehrnoosh [4 ]
机构
[1] Islamic Azad Univ, Khorramabad Branch, Fac Engn, Khorramabad, Iran
[2] Univ Teknol Malaysia, Fac Elect Engn, Johor Baharu, Malaysia
[3] Bu Ali Sina Univ, Fac Engn, Hamadan, Iran
[4] Lorestan Univ, Fac Engn, Khorramabad, Iran
关键词
Bees algorithm; global solar radiation; empirical coefficients; statistical regression techniques; empirical-based models; intelligent-based models; SUNSHINE DURATION; NEURAL-NETWORKS; MODEL; PARAMETERS; PSO;
D O I
10.1002/ep.11858
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Measurement of solar radiance demands expensive devices to be used. Alternatively, estimator models are used instead. In this article, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation (GSR) on a horizontal surface. The proposed method uses Bees algorithm as a heuristic and population-based search technique. The best coefficients of linear and nonlinear empirical models and GSR are calculated for seven different climate regions of Iran using proposed algorithm written in MATLAB software. The results of the proposed method are compared with other techniques. The result shows that the proposed method is more accurate in estimating the monthly average daily GSR. (C) 2013 American Institute of Chemical Engineers Environ Prog, 33: 1042-1050, 2014
引用
收藏
页码:1042 / 1050
页数:9
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