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A method for the generation of typical meteorological year data using ensemble empirical mode decomposition for different climates of China and performance comparison analysis

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  • Fan, Xinying

Abstract

The typical meteorological year (TMY) is one of the key factors to accurately estimate building energy consumption and analysis indoor environment. Therefore, high-performance TMY is crucial. A new TMY generation method based on empirical mode decomposition (EEMD) in this paper was put forward for different climates of China. The results show that the proposed method effectively improves the representation of TMY compared with traditional methods, especially for solar radiation and wind speed data. Finally, this paper analyzed the impact of TMY using EEMD on the results of building environmental analysis. The simulation result has showed that the TMY generated by the EEMD effectively reduced the relative average deviation for the estimation of the building energy consumption compared with other methods. This study further uses the method to obtain the daily weather database for selected cities in different climate regions of China.

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  • Fan, Xinying, 2022. "A method for the generation of typical meteorological year data using ensemble empirical mode decomposition for different climates of China and performance comparison analysis," Energy, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:energy:v:240:y:2022:i:c:s0360544221030711
    DOI: 10.1016/j.energy.2021.122822
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