Open Access
Issue |
E3S Web Conf.
Volume 520, 2024
4th International Conference on Environment Resources and Energy Engineering (ICEREE 2024)
|
|
---|---|---|
Article Number | 04029 | |
Number of page(s) | 5 | |
Section | Research on Energy Planning and Management and Energy Economy Strategy | |
DOI | https://doi.org/10.1051/e3sconf/202452004029 | |
Published online | 03 May 2024 |
- B. Wu, and H. Gao, “Analysis of carbon emission reduction effect of "Dual Control" policy of energy consumption,” Energy of China, 2021, 43, 6, pp. 39– 45. [Google Scholar]
- I. J. Hall, R. R. Prairie, H. E. Anderson, E. C. Boes, “Generation of a typical meteorological years for 26 SOLMET stations,” United States: N. p., 1978, pp. 669–671. [Google Scholar]
- M. William, and U. Ken, “User's Manual for TMY2s- Typical Meteorological Years,” United States: N. p., 1995. [Google Scholar]
- D. Pissimanis, G. Karras, V. Notaridou, K. Gavra, “The Generation of a Typical Meteorological Year for the City of Athens. Solar Energy,” 1988, 40, 5, pp.405–411. [Google Scholar]
- A. K. Soteris, “Generation of Typical Meteorological Year (TMY -2) for Nicosia, Cyprus,” Renewable Energy, 2003, 28, 15, pp. 2317–2334. [CrossRef] [Google Scholar]
- S.O. Olayinka, S.A. Muyiwa, M.O. Olanrewaju, O.F. Richard, “Generation of a typical meteorological year for North-east, Nigeria,” Applied Energy, 2013, 112, pp. 152–159. [CrossRef] [Google Scholar]
- Z. Shen, H. Tan, S. Lv, E. Kozuo, “Research on the typical meteorological year data of Shanghai for the building energy consumption calculation,” Heating Ventilating & Air Conditioning, 2010, 40, 1, pp.89–94. [Google Scholar]
- J. Sun, Z. Li, F. Xiao, J. Xiao, “Generation of typical meteorological year for integrated climate based daylight modelling and building energy simulation,” Renewable Energy, 2020, 160, pp. 721–729. [CrossRef] [Google Scholar]
- H. Li, A. Wang, Y. Hu, J. Huang, S. Wang, L. Yang, “Application of typical meteorological years and untypical meteorological years in building energy consumption simulation. Building Energy,” EFFICIENCY, 2021, 49, 11, pp.80–86. [Google Scholar]
- H. Mirata, B. Anahita, L. Bruno, “A systematic approach in constructing typical meteorological year weather files using machine learning,” Energy and Buildings, 2020, 226, 1, pp. 110375. [CrossRef] [Google Scholar]
- Meteorological data department of National Meteorological Information Centre. “Special meteorological data set for building thermal environment analysis in China,” China Construction Industry Press, 2005. [Google Scholar]
- Ministry of Housing and Urban-Rural Development of the People's Republic of China. “Standard for meteorological parameters of building energy conservation,” China Construction Industry Press, 2014, JGJ / T 346-2014. [Google Scholar]
- R.R. Fan, “Study on the composition of "extreme weather year" for building dynamic load and energy consumption simulation,” Chongqing: Chongqing University, 2015. [Google Scholar]
- S.Y. Guo, D. Yan, C.X. Gui, “The typical hot year and typical cold year for modeling extreme events impacts on indoor environment: A Generation Method and Case Study,” Building Simulation, 2020,13, pp.543–558. [CrossRef] [Google Scholar]
- State Administration of market supervision and State Standardization Administration Committee. “General rules for calculation of comprehensive energy consumption,” 2020, Beijing: China Standards Press, GB/T 2589-2020. [Google Scholar]
- Z.L. Song, and J. Zhang, “Research on the working principle and test method of the sensors in new type of Automatic Weather Station,” Process Automation Instrumentation, 2018,39, 7, pp.78–81. [Google Scholar]
- H.Z. Pan, and B. Yong, “Design of data monitoring system for ground meteorological observation station based on 5G communication,” Computer Measurement & Control, 2021,29, 6, pp. 30–34. [Google Scholar]
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