Estimation of daily and monthly diffuse radiation from measurements of global solar radiation a case study across China

RENEWABLE ENERGY

卷:126

Article

Wang, Hong¹  Sun, Fubao^1,2,3,4  Wang, Tingting^1,5  Liu, Wenbin¹ 

[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China

[2] Hexi Univ, Res Sch Qilian Mt Ecol, Zhangye City 734000, Gansu, Peoples R China

[3] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China

[4] Chinese Acad Sci, Ctr Water Resources Res, Beijing 100101, Peoples R China

[5] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

关键词: Diffuse radiation;    Global solar radiation;    Empirical regression;    China;   

DOI  :  10.1016/j.renene.2018.03.029

来源: Elsevier

【 摘 要 】

With increasing demand for energy, broaden renewable energy of income and reduce expenditure is becoming more and more important. Diffuse radiation (R-d) is an important consideration in building energy saving. Hundreds of methods were developed to calculate Rd because it is seldom available in many countries and its spatial-pattern is strongly station-dependent. There are only 13 stations that monitor both global solar radiation (R-s) and R-d after 1993 across China. Based on 812640 measurements of daily R-s and R-d collected from 80 stations across China during 1957-2014, we wished to calibrate and validate a simple approach, which can be easily used to predict R-d over both daily and monthly periods for all locations in China and gave the accurate values of parameters. The approach, of the case study method, is based on R-s and extra-terrestrial solar radiance (R-a). Results showed that the daily method can be employed well, while the monthly approach was applied well in the Southern Region (SR) only. The monthly approach of the Northern Region (NR) was improved using its regional characteristics. The methods achieved can effectively estimate R-d and strongly apply in engineering for only two parameters, which accurate values for all stations has been offered. (C) 2018 Elsevier Ltd. All rights reserved.

【 授权许可】

Free