Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/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
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ISSN | 1364-0321 |
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. |
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