Combination of Hargreaves method and linear regression as a new method to estimate solar radiation in Perlis, Northern Malaysia

被引:29
作者
Daut, I. [1 ]
Irwanto, M. [1 ]
Irwan, Y. M. [1 ]
Gomesh, N. [1 ]
Ahmad, N. S. [1 ]
机构
[1] Univ Malaysia Perlis, Sch Elect Syst Engn, Kangar 01000, Malaysia
关键词
Solar radiation; Temperature; Hargreaves method; Linear regression; Statistic analysis; METEOROLOGICAL DATA; AIR-TEMPERATURE;
D O I
10.1016/j.solener.2011.08.026
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The best way to obtain the solar radiation data of a particular place of interest (POI) is to measure at the specific site continuously and accurately over the long term. However, due to financial, maintenance, calibration requirement of the measuring equipment or institutional limitations, these data are absent, incomplete or inaccessible in most areas of the world. Based on meteorological data from Chuping Station, Perlis which is at Northern Malaysia, there were several missing data of solar radiation for the year 2007 and 2008. This paper presents a new method to estimate the solar radiation which is a combination of Hargreaves method and linear regression. Normally, both regression coefficients, a and b of the linear regression are found based on the measured data, but using the proposed method, both regression coefficients based on the Hargreaves method with the correlated parameter, x is the difference of daily temperature. This paper also presents the basic knowledge of Hargreaves method before the proposed method is implemented. As validation, those solar radiation data that are measured by Chuping Station for the year 2006 and by Electrical Energy and Industrial Electronic System (EEIES) Cluster Station for the month of March June 2011 and their estimated solar radiation data are compared and analyzed using coefficient of residual mass (CRM), root mean squared error (RMSE), Nash-Sutcliffe equation (NSE) and percentage error (e). The statistical analysis of the average monthly measured solar radiation data for the past 26 years (1979-2006) is compared with the estimated solar radiation data for 3 years (2006-2008). The proposed method result shows that the value of CRM is closer to zero which indicates that the proposed method is perfectly estimated, the values of RMSE are low value, this indicates that the method performs well, the value of NSE is closer to 1 which indicates that the estimated solar radiation match perfectly with the measured data taken for the past 26 years, the value of e is closer to zero which indicates that the proposed method is acceptable and applicable. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2871 / 2880
页数:10
相关论文
共 20 条
[1]  
Almorox J., 2003, ENERGY CONVERSION MA, V45, P1529
[2]   Estimation of monthly solar radiation from measured air temperature extremes [J].
Bandyopadhyay, A. ;
Bhadra, A. ;
Raghuwanshi, N. S. ;
Singh, R. .
AGRICULTURAL AND FOREST METEOROLOGY, 2008, 148 (11) :1707-1718
[3]  
Chen R, 2003, ENERGY CONVERSION MA, V45, P1759
[4]   New methods to estimate global radiation based on meteorological data in China [J].
Chen, Rensheng ;
Kang, Ersi ;
Lu, Shihua ;
Yang, Jianping ;
Ji, Xibin ;
Zhang, Zhihui ;
Zhang, Jishi .
ENERGY CONVERSION AND MANAGEMENT, 2006, 47 (18-19) :2991-2998
[5]   Equations for estimating global solar radiation in data sparse regions [J].
Chineke, Theo Chidiezie .
RENEWABLE ENERGY, 2008, 33 (04) :827-831
[6]   SOLAR-RADIATION ESTIMATES IN MALAYSIA [J].
CHUAH, DGS ;
LEE, SL .
SOLAR ENERGY, 1981, 26 (01) :33-40
[7]  
Daut I., 2009, INT C EL EN IND EL S
[8]  
Gavalian P., 2005, AGR WATER MANAGE, V81, P257
[9]  
HARGREAVES GH, 1982, J IRR DRAIN DIV-ASCE, V108, P225
[10]  
Inci T. T., 1998, ENERGY CONVERSION MA, V40, P1577