Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.rser.2017.08.037 |
Comparison of deterministic and data-driven models for solar radiation estimation in China | |
Qin, Wenmin1; Wang, Lunche2,3; Lin, Aiwen1; Zhang, Ming4; Xia, Xiangao3,6; Hu, Bo5; Niu, Zigeng2 | |
通讯作者 | Wang, Lunche |
来源期刊 | RENEWABLE & SUSTAINABLE ENERGY REVIEWS
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ISSN | 1364-0321 |
出版年 | 2018 |
卷号 | 81页码:579-594 |
英文摘要 | Solar radiation is an indispensable input for many applications, contributing to different fields, including energy, meteorology, ecology, agriculture and industry. A lot of parameterization schemes have been developed for estimating solar radiation in sites around the world. This paper presented a comparative study on the performances of four shortwave solar radiation (SSR) models in different climates, including Yang’s hybrid model (YHM), an efficient physically based model (EPP), an hourly solar radiation model (HSRM) and a neural network model (ANNM). Daily meteorological variables observed at 837 stations in China were used as model inputs for YHM and ANNM. MODIS atmospheric and land products (MOD08_D3, MYD08_D3, MOD08_M3, MYD08M3, MOD09CMG, and MYD09CMG) were used to derive the required parameters for EPP and HSRM. Cloud fraction and solar zenith angle were found to be the major parameters influencing the model accuracies. The results indicated that YHM performed superior to EPP, ANNM and HSRM with daily mean RMSE of 2.414, 2.535, 2.855 and 3.645 MJm(-2)day(-1), respectively. The monthly mean RMSE for all models were generally higher in July (3.37 MJm(-2)day(-1)) and lower in January (1.997 MJm(-2)day(-1)). It was observed that the monthly mean RMSE was 2.95 MJm(-2) day(-1) in humid areas, while it is 2.773 MJm(-2)day(-1) in semi-arid areas. Monthly and annual mean SSR (ASSR) during 2002-2015 were calculated to reveal the spatial and temporal variations of SSR across China using daily meteorological data, MOD08_M3 and MOD08_M3 products based on YHM and EPP models. The result showed that there was not obvious variation trends for ASSR in China, the largest value (14.521 MJm(-2)day(-1)) was observed in 2003, while the smallest ASSR (14.182 MJm(-2)day(-1)) was in 2014; the ASSR values were generally higher in Qinghai-Tibet and lower in northeastern China. |
英文关键词 | Solar radiation Deterministic model Data-driven model Comparison China |
类型 | Review |
语种 | 英语 |
国家 | Peoples R China |
收录类别 | SCI-E |
WOS记录号 | WOS:000417070500043 |
WOS关键词 | ARTIFICIAL NEURAL-NETWORK ; SUPPORT VECTOR MACHINE ; PHOTOSYNTHETICALLY ACTIVE RADIATION ; BROAD-BAND MODELS ; EMPIRICAL-MODELS ; IRRADIANCE PREDICTIONS ; EARTHS SURFACE ; HYBRID MODEL ; MODIS ; VALIDATION |
WOS类目 | Green & Sustainable Science & Technology ; Energy & Fuels |
WOS研究方向 | Science & Technology - Other Topics ; Energy & Fuels |
来源机构 | 中国科学院大气物理研究所 ; 南京信息工程大学 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/212705 |
作者单位 | 1.Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China; 2.China Univ Geosci, Lab Crit Zone Evolut, Sch Earth Sci, Lumo Rd 388, Wuhan 430074, Hubei, Peoples R China; 3.Chinese Acad Sci, Inst Atmospher Phys, Key Lab Middle Atmosphere & Global Environm Obser, Beijing 100029, Peoples R China; 4.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China; 5.Chinese Acad Sci, State Key Lab Atmospher Boundary Phys & Atmospher, Inst Atmospher Phys, Beijing 100029, Peoples R China; 6.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Qin, Wenmin,Wang, Lunche,Lin, Aiwen,et al. Comparison of deterministic and data-driven models for solar radiation estimation in China[J]. 中国科学院大气物理研究所, 南京信息工程大学,2018,81:579-594. |
APA | Qin, Wenmin.,Wang, Lunche.,Lin, Aiwen.,Zhang, Ming.,Xia, Xiangao.,...&Niu, Zigeng.(2018).Comparison of deterministic and data-driven models for solar radiation estimation in China.RENEWABLE & SUSTAINABLE ENERGY REVIEWS,81,579-594. |
MLA | Qin, Wenmin,et al."Comparison of deterministic and data-driven models for solar radiation estimation in China".RENEWABLE & SUSTAINABLE ENERGY REVIEWS 81(2018):579-594. |
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