WEATHER CLASSIFICATION METHOD BASED ON ATMOSPHERIC TRANSPARENCY COEFFICIENT

Chen Long; Sun Wenzhe; Yu Guojun

doi:10.19912/j.0254-0096.tynxb.2020-1239

PDF(1341 KB)

Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (7) : 174-179. DOI: 10.19912/j.0254-0096.tynxb.2020-1239

WEATHER CLASSIFICATION METHOD BASED ON ATMOSPHERIC TRANSPARENCY COEFFICIENT

Chen Long, Sun Wenzhe, Yu Guojun

Author information +

History +

Abstract

The application of solar radiation models is, to some extent, limited by the randomness of weather variations and complicated and various influencing factors. This paper discussed the feasibility of using the atmospheric transparency coefficient as a basis for weather classification, extended the definition of the coefficient of atmospheric transparency to complex weather conditions and corrected the influence on the solar altitude angle. Further, a weather classification method based on the atmospheric transparency coefficient was proposed, and its application in the direct solar radiation models was listed to illustrate the effectiveness of this method.

Key words

weather classification / forecasting / solar radiation / atmospheric transparency coefficient

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Chen Long, Sun Wenzhe, Yu Guojun. WEATHER CLASSIFICATION METHOD BASED ON ATMOSPHERIC TRANSPARENCY COEFFICIENT[J]. Acta Energiae Solaris Sinica. 2022, 43(7): 174-179 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1239

References

[1] PEREIRA M C, RABL A.The average distribution of solar radiation correlations between diffuse and hemispherical and between daily and hourly insolation values[J]. Solar energy, 1979, 22(2): 155-164.
[2] 曹双华, 曹家枞. 太阳逐时总辐射混沌优化神经网络预测模型研究[J]. 太阳能学报, 2006, 27(2): 164-169.
CAO S H, CAO J C.Study of chaos optimization neural networks for the forecast of hourly total solar irradiation[J]. Acta energiae solaris sinica, 2006, 27(2): 164-169.
[3] 苏高利, 柳钦火, 邓芳萍, 等. 基于LS-SVM方法的晴空逐时太阳辐射模型[J]. 北京师范大学学报(自然科学版), 2007, 43(3): 274-278.
SU G L, LIU Q H, DENG F P, et al.The hourly global clear sky radiation model based on the least squares support vector machines[J]. Journal of Beijing Normal University(natural science), 2007, 43(3): 274-278.
[4] 田翠霞, 黄敏, 朱启兵. 基于EMD-LMD-LSSVM联合模型的逐时太阳辐照度预测[J]. 太阳能学报, 2018, 39(2): 504-512.
TIAN C X, HUANG M, ZHU Q B.Hourly solar irradiance forecast based on EMD-LMD-LSSVM joint model[J]. Acta energiae solaris sinica, 2018, 39(2): 504-512.
[5] 曹其梦, 于瑛, 杨柳. 太阳逐时总辐射计算模型适用性分析——以我国部分地区为例[J]. 太阳能学报, 2018, 39(4): 917-924.
CAO Q M, YU Y, YANG L.Applicability analysis of hourly total solar radiation calculation model-Taking some regions of China as example[J]. Acta energiae solaris sinica, 2018, 39(4): 917-924.
[6] 李芬, 刘迪, 闫全全, 等. 天文、气象环境因子与散射比关系的建模分析[J]. 太阳能学报, 2020, 41(2): 203-209.
LI F, LIU D, YAN Q Q, et al.Analysis on relationship between diffuse irradiation ratio and astronomical and meteorological environmental factors[J]. Acta energiae solaris sinica, 2020, 41(2): 203-209.
[7] 徐祝龄. 气象学[M]. 北京: 气象出版社, 1994: 190-204.
XU Z L.Meteorology[M]. Beijing:China Meteorological Press, 1994: 190-204.
[8] 王炳忠, 潘根娣. 我国的大气透明度及其计算[J]. 太阳能学报, 1981, 2(1): 13-22.
WANG B Z, PAN G D.The transparency of atmosphere over China and its computation[J]. Acta energiae solaris sinica, 1981, 2(1): 13-22.
[9] 中国气象局气象信息中心气象资料室, 清华大学建筑技术科学系. 中国建筑热环境分析专用气象数据集[M]. 北京: 中国建筑工业出版社, 2005: 51-57.
China Meteorological Information Center, Department of Building Science & Technology of Tsinghua University. Special meteorological data set for China building thermal environment analysis[M]. Beijing:China Architecture & Building Press, 2005: 51-57.
[10] 彦启森, 赵庆珠. 建筑热过程[M]. 北京: 中国建筑工业出版社, 1986: 6-8.
YAN Q S, ZHAO Q Z.Building thermal process[M]. Beijing: China Architecture & Building Press, 1986: 6-8.
[11] CHANG C C, LIN C J.LIBSVM: A library for support vector machines[J]. ACM transactions on intelligent systems and technology, 2011, 2(3): 1-27.