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Identifying a suitable hourly solar diffuse fraction model to generate the typical meteorological year for building energy simulation application

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  • Huang, Kuo-Tsang

Abstract

As cooling and heating energy consumptions of buildings are closely related to outdoor climate variations, the reliability of building energy simulation results is significantly influenced by the accuracy of weather data being used. We intend to construct a new typical meteorological year (TMY) for Taipei. As no beam or diffuse solar irradiance data have been recorded at local weather stations, a preliminary study on the influences of currently available hourly solar diffuse fraction models (DFMs) to the building cooling loads was performed. A 2.30%–5.18% range of annual cooling load variation was observed, which drove a need for searching suitable DFMs. To this end, the observed diffuse irradiance data of an in-situ experiment was compared to the DFM modeled values to identify the suitable DFM. It was found that Kuo’s model, which has its coefficient been adapted to the local weather and further uses solar altitude, the daily clearness index as predicting variables, performed best and was used herein. The representativeness against the long-term climate of the three antiquated TMYs and the new one was discussed with a simulation-based comparison from 12 existing buildings. The reliability and accuracy of the new TMY in representing the local climate conditions are much improved.

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  • 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.
    • Handle: RePEc:eee:renene:v:157:y:2020:i:c:p:1102-1115
    DOI: 10.1016/j.renene.2020.05.094
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    5. De Masi, Rosa Francesca & Gigante, Antonio & Ruggiero, Silvia & Vanoli, Giuseppe Peter, 2021. "Impact of weather data and climate change projections in the refurbishment design of residential buildings in cooling dominated climate," Applied Energy, Elsevier, vol. 303(C).
    6. Lin, Chun-Tin & Chang, Keh-Chin & Chung, Kung-Ming, 2023. "Re-modeling the solar diffuse fraction in Taiwan on basis of a typical-meteorological-year data," Renewable Energy, Elsevier, vol. 204(C), pages 823-835.
    7. Hassan, Muhammed A. & Akoush, Bassem M. & Abubakr, Mohamed & Campana, Pietro Elia & Khalil, Adel, 2021. "High-resolution estimates of diffuse fraction based on dynamic definitions of sky conditions," Renewable Energy, Elsevier, vol. 169(C), pages 641-659.
    8. Jahns, Christopher & Osinski, Paul & Weber, Christoph, 2023. "A statistical approach to modeling the variability between years in renewable infeed on energy system level," Energy, Elsevier, vol. 263(PA).

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