Arid
DOI10.1016/j.rser.2018.06.009
Evaluation of sunshine-based models for predicting diffuse solar radiation in China
Feng, Lan1; Lin, Aiwen1; Wang, Lunche2; Qin, Wenmin2; Gong, Wei3
通讯作者Lin, Aiwen ; Wang, Lunche
来源期刊RENEWABLE & SUSTAINABLE ENERGY REVIEWS
ISSN1364-0321
出版年2018
卷号94页码:168-182
英文摘要

Accurate observation and understanding of diffuse radiation is of vital importance for solar energy applications. Numerous empirical models have been developed for estimating solar radiation in regional and global scales, owing to the relatively sparse radiation measurements. The main objective of this study was to conduct a comprehensive evaluation of 15 typical empirical models for estimating diffuse radiation in different climate zones over mainland China. The result showed that the model in form of second order polynomial performed superior than other models, with mean MBE, MAE, MARE, RMSE, RRMSE, t-stat, STD, and R at all 17 CMA stations were -0.125 MJ m(-2) day(-1), 1.331 MJ m(-2) day-1, 0.208 MJ m(-2) day(-1),1.807 MJ m(-2) day(-1), 24.889%, 10.866, 0.941 MJ m(-2) day-1, and 0.792, respectively. By contrast, the model in form of fractional first order polynomial showed the poorest performance than other models, with mean MAE, MARE, RMSE, RRMSE, t-stat, STD, and R of-0.699 MJ m(-2) day(-1), 2.508 MJ m(-2)day(-1), 0.397 MJ m(-2) day(-1), 6.779 MJ m(-2) day(-1), 102.716%, 6.709, 1.773 MJ m(-2) day(-1), and 0.519, respectively. All models generally showed poor accuracies in arid areas with warm-temperate climate, due to the frequent dust occurrences in the air. The estimation errors in Qinghai-Tibet Plateau were also relatively larger, owing to the strong heating atmosphere there. This study would assist in the selection of the most appropriate models for solar energy applications.


英文关键词Sunshine-based models Diffuse solar radiation China
类型Review
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000446310000012
WOS关键词ARTIFICIAL NEURAL-NETWORKS ; EMPIRICAL-MODELS ; SENSITIVITY-ANALYSIS ; INCLINED SURFACES ; GLOBAL IRRADIANCE ; SATELLITE IMAGES ; FRACTION ; METHODOLOGY ; PERFORMANCE ; REGRESSION
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/2XILL650/212716
作者单位1.Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China;
2.China Univ Geosci, Sch Earth Sci, Lab Crit Zone Evolut, Wuhan 430074, Hubei, Peoples R China;
3.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China
推荐引用方式
GB/T 7714
Feng, Lan,Lin, Aiwen,Wang, Lunche,et al. Evaluation of sunshine-based models for predicting diffuse solar radiation in China[J],2018,94:168-182.
APA Feng, Lan,Lin, Aiwen,Wang, Lunche,Qin, Wenmin,&Gong, Wei.(2018).Evaluation of sunshine-based models for predicting diffuse solar radiation in China.RENEWABLE & SUSTAINABLE ENERGY REVIEWS,94,168-182.
MLA Feng, Lan,et al."Evaluation of sunshine-based models for predicting diffuse solar radiation in China".RENEWABLE & SUSTAINABLE ENERGY REVIEWS 94(2018):168-182.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Feng, Lan]的文章
[Lin, Aiwen]的文章
[Wang, Lunche]的文章
百度学术
百度学术中相似的文章
[Feng, Lan]的文章
[Lin, Aiwen]的文章
[Wang, Lunche]的文章
必应学术
必应学术中相似的文章
[Feng, Lan]的文章
[Lin, Aiwen]的文章
[Wang, Lunche]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。