OBTAINING METHODS OF TYPICAL METEOROLOGICAL YEAR DATA FOR AREAS OUTSIDE METEOROLOGICAL OBSERVATION STATIONS

Li Honglian; Yang Yi; Fu Yuxi; Wang Shangyu; Zhang Jie; Yang Liu

doi:10.19912/j.0254-0096.tynxb.2020-1318

PDF(1814 KB)

Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (8) : 150-156. DOI: 10.19912/j.0254-0096.tynxb.2020-1318

OBTAINING METHODS OF TYPICAL METEOROLOGICAL YEAR DATA FOR AREAS OUTSIDE METEOROLOGICAL OBSERVATION STATIONS

Li Honglian¹, Yang Yi¹, Fu Yuxi¹, Wang Shangyu², Zhang Jie¹, Yang Liu²

Author information +

History +

Abstract

At present the design and development of China's renewable energy buildings, usually using the typical meteorological year data on behalf of the local solar radiation and climate characteristics because some areas in China have no long-term observation data. However, the lack of basic meteorological elements may cause the passive situation of the architectural design and be unable to accurately provide outdoor basis data scientifically. In order to solve this problem, based on the national benchmark and basic, the original record data of general weather stations using the inverse distance weighted （IDW） interpolation method and gradient inverse distance weighted （GIDW） interpolation method, the error analysis of the experimental results is carried out. Typical Meteorological Year（TMY）data acquisition methods outside the northwest and southeast area meteorological observation stations are researched and developed. By using mathematical model to generate specific hourly data. The results show that the variation trend of the meteorological data obtained by the GIDW method is similar to that of the actual data. At the same time, after considering the influence of altitude, the interpolation error of the GIDW method is smaller than that of the IDW method. The hourly data is processed, and the generated data of the measured point is in good agreement with the actual hourly value.

Key words

typical meteorological year / hourly data / solar radiation / non-standard station

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Li Honglian, Yang Yi, Fu Yuxi, Wang Shangyu, Zhang Jie, Yang Liu. OBTAINING METHODS OF TYPICAL METEOROLOGICAL YEAR DATA FOR AREAS OUTSIDE METEOROLOGICAL OBSERVATION STATIONS[J]. Acta Energiae Solaris Sinica. 2022, 43(8): 150-156 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1318

References

[1] 陈龙. 关于绿色建筑中可再生能源利用的思考[J]. 绿色环保建材, 2020, 166(12): 29-30.
CHENG L.Reflections on the use of renewable energy in green buildings[J]. Green building materials, 2020, 166(12): 29-30.
[2] 郭建峰. 可再生能源技术在中国绿色建筑中的应用[J]. 北京工业职业技术学院学报, 2021, 20(1): 24-27.
GUO J F.Application of renewable energy technology in green building in China[J]. Journal of Beijing Polytechnic College, 2021, 20(1): 24-27.
[3] ECEVIT A, AKINOGLU B G, AKSOV B.Generation of a typical meteorological year using sunshine duration data[J]. Energy, 2002, 27(10): 947-954.
[4] 李红莲, 杨柳, 侯立强, 等. 建筑能耗模拟用典型年气象参数的选取方法[J]. 太阳能学报, 2016, 37(9): 2408-2414.
LI H L, YANG L, HOU L Q, et al.Selection method of typical annual meteorological parameters for building energy consumption simulation[J]. Acta energiae solaris sinica, 2016, 37(9): 2408-2414.
[5] 刘婧, 李红莲, 吕凯琳, 等. 不同统计时长对典型气象年选取结果的影响[J]. 工业建筑, 2020, 50(7): 95-100, 203.
LIU J, LI H L, LYU K L, et al.The influence of different statistical durations on the selection results of typical meteorological years[J]. Industrial construction, 2020, 50(7): 95-100, 203.
[6] PRICE D T, MCKENNEY D W, NALDER I A, et al.A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data[J]. Agricultural and forest meteorology, 2000, 101(2-3): 81-94.
[7] 林忠辉, 莫兴国, 李宏轩, 等. 中国陆地区域气象要素的空间插值[J]. 地理学报, 2002, 57(1): 47-56.
LIN Z H, MO X G, LI H X, et al.Spatial interpolation of terrestrial meteorological elements in China[J]. Acta geographica sinica, 2002, 57(1): 47-56.
[8] 李军, 游松财, 黄敬峰. 中国1961—2000年月均值气温空间插值方法与空间分布[J]. 生态环境, 2006, 15(1): 109-104.
LI J, YOU S C, HUANG J F.Interpolation method and spatial distribution of mean air temperature in 1961—2000 years in China[J]. The ecological environment, 2006, 15(1): 109-104.
[9] 徐超, 吴大千, 张治国. 山东省多年气象要素空间插值方法比较研究[J]. 山东大学学报(理学版), 2008, 43(3): 1-5.
XU C, WU D Q, ZHANG Z G.Comparative study on spatial interpolation methods of meteorological elements in Shandong Province[J]. Journal of Shandong University(science edition), 2008, 43(3): 1-5.
[10] NALDER I A, WEIN R W.Spatial interpolation of climatic normals: test of a new method in the Canadian boreal forest[J]. Agricultural and forest meteorology, 1998, 92(4): 211-225.
[11] LU G Y, WONG D W.An adaptive inverse-distance weighting spatial interpolation technique[J]. Computers and geosciences, 2008, 34(9): 1044-1055.
[12] 潘耀忠, 龚道溢, 邓磊, 等. 基于DEM的中国陆地多年平均温度插值方法[J]. 地理学报, 2004, 59(3): 366-374.
PAN Y Z, GONG D Y, DENG L, et al.Interpolation method of Multi-year mean temperature of Chinese Land based on DEM[J]. Chinese journal of geography, 2004, 59(3): 366-374.
[13] 封志明, 杨艳昭, 丁晓强, 等. 气象要素空间插值方法优化[J]. 地理研究, 2004, 23(3): 357-364.
FENG Z M, YANG Y Z, DING X Q, et al.Optimization of spatial interpolation method for meteorological Elements[J]. Geographical research, 2004, 23(3): 357-364.
[14] JGJ/T 346—2014, 建筑节能气象参数标准[S].
JGJ/T346—2014, Meteorological parameters standard for building energy conservation[S].
[15] JGJ134—2010, 夏热冬冷地区居住建筑节能设计标准[S].
JGJ134—2010, Design standard for energy conservation of residential buildings in hot summer and cold winter areas[S].
[16] JGJ75—2012, 夏热冬暖地区居住建筑节能设计标准[S].
JGJ75—2012, Design standard for energy conservation of residential buildings in hot Summer and warm winter areas[S].
[17] GB 50189—2015, 公共建筑节能设计标准[S].
GB 50189—2015, Design standard for energy conservation of public buildings[S].
[18] HALL I J.Generation of typical meteorological years for 26 SOL2MET stations[C]//Proceedings of the 1978 Annual Meeting of the American Section of the International Solar Energy Society, Denver, 1978: 669-671.
[19] WILLIAM M, KEN U, User's manual for TMY2's[R]. National renewable energy laboratory, 1995.
[20] ANDERSEN B, EIDORFF S, LUND H, et al.Meteorological data for design of building and installation[R]. A reference year (extract) report 66, 2nd ed. Denmark: Thermal Insulation Laboratory, 1977.
[21] 张晴原, Joe Huang.中国建筑用标准气象数据手册[M]. 北京: 中国建筑工业出版社, 2012: 17-18.
ZHANG Q Y, JOE HUANG.Meteorological data manual of Chinese construction standards[M]. Beijing: China Building Industry Press, 2012: 17-18.
[22] 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: 55-56.
Department of building technology and science, Tsinghua University, meteorological information center, China meteorological administration. meteorological data set for China building Thermal environment analysis[M]. Beijing: China Building Industry Press, 2005: 55-56.
[23] LIU Y, WAN K K W, LI D H W, et al. A new method to develop typical weather years in different climates for building energy use studies[J]. Energy, 2011, 36(10): 6121-6129.
[24] JOHNSON M E, FITZPATRICK E A.A comparison of two methods of estimating a mean diurnal temperature curve during the daylight hours[J]. Theoretical and applied climatology, 1977, 25(3): 251-263.
[25] PARTON W J, LOGAN J A.A model for diurnal variation in soil and air temperature[J]. Agricultural meteorology, 1981, 23: 205-216.
[26] 于瑛, 杨柳, 陈猛, 等. 日散射辐射推算模型在中国的适用性研究[J]. 太阳能学报, 2018, 39(11): 3005-3013.
YU Y, YANG L, CHEN M, et al.Study on the applicability of the extrapolation model of daily scattered radiation in China[J]. Acta energiae solaris sinica, 2018, 39(11): 3005-3013.
[27] 曹其梦, 杨柳, 于瑛. 日散射辐射模型经验系数确定方法[J]. 哈尔滨工业大学学报, 2020, 52(4): 187-194.
CAO Q M, YANG L, YU Y.Methods for determining the empirical coefficients of daily scattered radiation model[J]. Journal of Harbin Institute of Technology, 2020, 52(4): 187-194.
[28] PAASSEN A V, LUO Q X.Weather data generator to study climate change on buildings[J]. Building services engineering research & technology, 2002, 23(4): 251-258.