干旱区生态环境知识资源中心(Arid): Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis

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DOI	10.1016/j.rser.2020.110087
	Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis
	Sun, Xixi; Bright, Jamie M.; Gueymard, Christian A.; Bai, Xinyu; Acord, Brendan; Wang, Peng
通讯作者	Bright, JM
来源期刊	RENEWABLE & SUSTAINABLE ENERGY REVIEWS
ISSN	1364-0321
EISSN	1879-0690
出版年	2021
卷号	135
英文摘要	Accurate estimations of clear-sky direct normal irradiance (DNIcs) and diffuse horizontal irradiance (DIFcs) are crucial in solar resources assessment. This study examines 95 and 88 popular clear-sky irradiance models for their worldwide estimation capability of DNIcs and DIFcs, respectively. Atmospheric inputs are from MERRA-2 reanalysis and irradiance observations for validation are extracted from 100 ground stations across five major Kodppen-Geiger climate zones. They consist of 24 million 1-min measurements of DINcs and 18.7 million 1-min measurements of DIFcs after quality control and clear-sky detection, during the 5-year period 2015-2019. Using principal component analysis, the performance of each clear-sky irradiance model is ranked separately among the five climate zones, as well as given a global rank. For the Equatorial, Arid, Temperate, Cold and Polar climates, it is found that HELIOSAT1-I, ESRA-I, REST2V9.1, REST2V9.1 and CLS, respectively, are the best DNIcs models, while MODIFIED IQBAL-C, HELIOSAT1-R, CALINOIU, MODIFIED IQBAL-C and PSI-REST are the best DIFcs models. On a global worldwide basis, the three top-ranking models are REST2V9.1, REST2V5 and MMAC-V2 for DNIcs, and MODIFIED IQBAL-C, PSI-REST and MRMV5 for DIFcs. The results and rankings presented are strictly relative to MERRA-2 input data, and should not be extrapolated to results from alternate sources of atmospheric data. This detailed validation exercise revealed inconsistent performance of many models across different climates, possibly due to insufficient training and/or over-fitting of empirical relationships. Codes of all clear-sky irradiance models in the public domain are available online on the Github repository JamieMBright/clear-sky-models.
英文关键词	Clear-sky irradiance Clear-sky model Validation Principal component analysis Direct normal irradiance Diffuse horizontal irradiance Kodppen-Geiger
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000592385400003
WOS关键词	DIRECT SOLAR TRANSMITTANCE ; BROAD-BAND MODELS ; PHOTOSYNTHETICALLY ACTIVE RADIATION ; AEROSOL OPTICAL DEPTH ; GLOBAL IRRADIANCE ; LINKE TURBIDITY ; ATMOSPHERIC TURBIDITY ; LUMINOUS EFFICACY ; TIME-SERIES ; VALIDATION
WOS类目	Green & Sustainable Science & Technology ; Energy & Fuels
WOS研究方向	Science & Technology - Other Topics ; Energy & Fuels
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/328029
作者单位	[Sun, Xixi; Wang, Peng] Beihang Univ, LMIB, Beijing, Peoples R China; [Sun, Xixi; Wang, Peng] Beihang Univ, Sch Math Sci, Beijing, Peoples R China; [Bright, Jamie M.] Natl Univ Singapore, Solar Energy Res Inst Singapore SERIS, Singapore 117574, Singapore; [Gueymard, Christian A.] Solar Consulting Serv, Colebrook, NH USA; [Bai, Xinyu] Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China; [Acord, Brendan] Syene Clean Energy, Hong Kong, Peoples R China; [Wang, Peng] Beihang Univ, Sch Microelect, Beijing, Peoples R China; [Wang, Peng] Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Sun, Xixi,Bright, Jamie M.,Gueymard, Christian A.,et al. Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis[J],2021,135.
APA	Sun, Xixi,Bright, Jamie M.,Gueymard, Christian A.,Bai, Xinyu,Acord, Brendan,&Wang, Peng.(2021).Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis.RENEWABLE & SUSTAINABLE ENERGY REVIEWS,135.
MLA	Sun, Xixi,et al."Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis".RENEWABLE & SUSTAINABLE ENERGY REVIEWS 135(2021).