IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v240y2022ics0360544221030711.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221030711
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.122822?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pusat, Saban & Ekmekçi, İsmail & Akkoyunlu, Mustafa Tahir, 2015. "Generation of typical meteorological year for different climates of Turkey," Renewable Energy, Elsevier, vol. 75(C), pages 144-151.
    2. Wang, Xia & Feng, Wei & Cai, Weiguang & Ren, Hong & Ding, Chao & Zhou, Nan, 2019. "Do residential building energy efficiency standards reduce energy consumption in China? – A data-driven method to validate the actual performance of building energy efficiency standards," Energy Policy, Elsevier, vol. 131(C), pages 82-98.
    3. Chan, A.L.S., 2016. "Generation of typical meteorological years using genetic algorithm for different energy systems," Renewable Energy, Elsevier, vol. 90(C), pages 1-13.
    4. Haixiang Zang & Miaomiao Wang & Jing Huang & Zhinong Wei & Guoqiang Sun, 2016. "A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China," Energies, MDPI, vol. 9(12), pages 1-19, December.
    5. Ohunakin, Olayinka S. & Adaramola, Muyiwa S. & Oyewola, Olanrewaju M. & Fagbenle, Richard O., 2013. "Generation of a typical meteorological year for north–east, Nigeria," Applied Energy, Elsevier, vol. 112(C), pages 152-159.
    6. Yang, Liu & Wan, Kevin K.W. & Li, Danny H.W. & Lam, Joseph C., 2011. "A new method to develop typical weather years in different climates for building energy use studies," Energy, Elsevier, vol. 36(10), pages 6121-6129.
    7. Smirnova, Elena & Kot, Sebastian & Kolpak, Eugeny & Shestak, Viktor, 2021. "Governmental support and renewable energy production: A cross-country review," Energy, Elsevier, vol. 230(C).
    8. Foucquier, Aurélie & Robert, Sylvain & Suard, Frédéric & Stéphan, Louis & Jay, Arnaud, 2013. "State of the art in building modelling and energy performances prediction: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 272-288.
    9. Jiang, Yingni, 2010. "Generation of typical meteorological year for different climates of China," Energy, Elsevier, vol. 35(5), pages 1946-1953.
    10. Wang, Ran & Feng, Wei & Wang, Lan & Lu, Shilei, 2021. "A comprehensive evaluation of zero energy buildings in cold regions: Actual performance and key technologies of cases from China, the US, and the European Union," Energy, Elsevier, vol. 215(PA).
    11. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Xiao-Yun Chen, 2015. "Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2655-2675, June.
    12. Janjai, S. & Deeyai, P., 2009. "Comparison of methods for generating typical meteorological year using meteorological data from a tropical environment," Applied Energy, Elsevier, vol. 86(4), pages 528-537, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Putra, I Dewa Gede Arya & Nimiya, Hideyo & Sopaheluwakan, Ardhasena & Kubota, Tetsu & Lee, Han Soo & Pradana, Radyan Putra & Alfata, Muhammad Nur Fajri & Perdana, Reza Bayu & Permana, Donaldi Sukma & , 2024. "Development of typical meteorological years based on quality control of datasets in Indonesia," Renewable Energy, Elsevier, vol. 221(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haixiang Zang & Miaomiao Wang & Jing Huang & Zhinong Wei & Guoqiang Sun, 2016. "A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China," Energies, MDPI, vol. 9(12), pages 1-19, December.
    2. Vincenzo Costanzo & Gianpiero Evola & Marco Infantone & Luigi Marletta, 2020. "Updated Typical Weather Years for the Energy Simulation of Buildings in Mediterranean Climate. A Case Study for Sicily," Energies, MDPI, vol. 13(16), pages 1-24, August.
    3. Sun, Jingting & Li, Zhengrong & Xiao, Fu & Xiao, Jianzhuang, 2020. "Generation of typical meteorological year for integrated climate based daylight modeling and building energy simulation," Renewable Energy, Elsevier, vol. 160(C), pages 721-729.
    4. Li, Honglian & Huang, Jin & Hu, Yao & Wang, Shangyu & Liu, Jing & Yang, Liu, 2021. "A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China," Energy, Elsevier, vol. 231(C).
    5. Oluwaseu Kilanko & Sunday O Oyedepo & Joseph O Dirisu & Richard O Leramo & Philip Babalola & Abraham K Aworinde & Mfon Udo & Alexander M Okonkwo & Marvelous I Akomolafe, 2023. "Typical meteorological year data analysis for optimal usage of energy systems at six selected locations in Nigeria," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 637-658.
    6. Kulesza, Kinga, 2017. "Comparison of typical meteorological year and multi-year time series of solar conditions for Belsk, central Poland," Renewable Energy, Elsevier, vol. 113(C), pages 1135-1140.
    7. Xinying Fan & Bin Chen & Changfeng Fu & Lingyun Li, 2020. "Research on the Influence of Abrupt Climate Changes on the Analysis of Typical Meteorological Year in China," Energies, MDPI, vol. 13(24), pages 1-16, December.
    8. Cui, Ying & Yan, Da & Hong, Tianzhen & Xiao, Chan & Luo, Xuan & Zhang, Qi, 2017. "Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China," Applied Energy, Elsevier, vol. 195(C), pages 890-904.
    9. Putra, I Dewa Gede Arya & Nimiya, Hideyo & Sopaheluwakan, Ardhasena & Kubota, Tetsu & Lee, Han Soo & Pradana, Radyan Putra & Alfata, Muhammad Nur Fajri & Perdana, Reza Bayu & Permana, Donaldi Sukma & , 2024. "Development of typical meteorological years based on quality control of datasets in Indonesia," Renewable Energy, Elsevier, vol. 221(C).
    10. Chan, A.L.S., 2016. "Generation of typical meteorological years using genetic algorithm for different energy systems," Renewable Energy, Elsevier, vol. 90(C), pages 1-13.
    11. Li, Honglian & Yang, Yi & Lv, Kailin & Liu, Jing & Yang, Liu, 2020. "Compare several methods of select typical meteorological year for building energy simulation in China," Energy, Elsevier, vol. 209(C).
    12. Tejero-González, Ana & Andrés-Chicote, Manuel & García-Ibáñez, Paola & Velasco-Gómez, Eloy & Rey-Martínez, Francisco Javier, 2016. "Assessing the applicability of passive cooling and heating techniques through climate factors: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 727-742.
    13. Pusat, Saban & Ekmekçi, İsmail & Akkoyunlu, Mustafa Tahir, 2015. "Generation of typical meteorological year for different climates of Turkey," Renewable Energy, Elsevier, vol. 75(C), pages 144-151.
    14. Huang, Kuo-Tsang, 2020. "Identifying a suitable hourly solar diffuse fraction model to generate the typical meteorological year for building energy simulation application," Renewable Energy, Elsevier, vol. 157(C), pages 1102-1115.
    15. Ohunakin, Olayinka S. & Adaramola, Muyiwa S. & Oyewola, Olanrewaju M. & Fagbenle, Richard O., 2013. "Generation of a typical meteorological year for north–east, Nigeria," Applied Energy, Elsevier, vol. 112(C), pages 152-159.
    16. Abreu, Edgar F.M. & Canhoto, Paulo & Prior, Victor & Melicio, R., 2018. "Solar resource assessment through long-term statistical analysis and typical data generation with different time resolutions using GHI measurements," Renewable Energy, Elsevier, vol. 127(C), pages 398-411.
    17. Carra, Elena & Ballestrín, Jesús & Polo, Jesús & Barbero, Javier & Fernández-Reche, Jesús, 2018. "Atmospheric extinction levels of solar radiation at Plataforma Solar de Almería. Application to solar thermal electric plants," Energy, Elsevier, vol. 145(C), pages 400-407.
    18. García, Ignacio & Torres, José Luis, 2018. "Temporal downscaling of test reference years: Effects on the long-term evaluation of photovoltaic systems," Renewable Energy, Elsevier, vol. 122(C), pages 392-405.
    19. Polo, Jesús & Alonso-Abella, Miguel & Martín-Chivelet, Nuria & Alonso-Montesinos, Joaquín & López, Gabriel & Marzo, Aitor & Nofuentes, Gustavo & Vela-Barrionuevo, Nieves, 2020. "Typical Meteorological Year methodologies applied to solar spectral irradiance for PV applications," Energy, Elsevier, vol. 190(C).
    20. Li, Shuai & Ma, Hongjie & Li, Weiyi, 2017. "Typical solar radiation year construction using k-means clustering and discrete-time Markov chain," Applied Energy, Elsevier, vol. 205(C), pages 720-731.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:240:y:2022:i:c:s0360544221030711. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.