Improving solar radiation estimation in China based on regional optimal combination of meteorological factors with machine learning methods-Reference-Cited by-同舟云学术

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Improving solar radiation estimation in China based on regional optimal combination of meteorological factors with machine learning methods

Published:2020-09 Issue: Volume:220 Page:113111
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

He Chuan,Liu Jiandong,Xu Fang,Zhang Teng,Chen Shang,Sun Zhe,Zheng Wenhui,Wang Runhong,He Liang,Feng Hao,Yu Qiang,He Jianqiang

Funder

Shanxi Provincial Key Research and Development Project

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference70 articles.

1. Estimation of daily global solar radiation from measured temperatures at Cañada de Luque, Córdoba, Argentina;Almorox;Renew Energy,2013

2. Variation in reference crop evapotranspiration caused by the Ångström-Prescott coefficient: Locally calibrated versus the FAO recommended;Liu;Agric Water Manage,2009

3. The sun’s total and spectral irradiance for solar energy applications and solar radiation models;Gueymard;Sol Energy,2004

4. Solar radiation management could be a game changer. Nat;Irvine;Clim Change,2014

5. Differences between observed and calculated solar radiations and their impact on simulated crop yields;Wang;Field Crop Res,2015

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