Journals / Journal of Thermal Engineering / 2026 / Volume: 8 Issue: 5

The effects of different typical meteorological year data on the heating and cooling demand of buildings: Case study of Turkiye

Uğur Acar(Republic of Turkey Ministry of Environment and Urbanization, Provincial Directorate of Osmaniye, Turkiye, 80000)0000-0002-6387-8641
Önder Kaşk(Department of Mechanical Engineering, Osmaniye Korkut Ata University, Osmaniye, Turkiye, 80000)0000-0002-7284-2093
Nehir Tokgöz(Department of Mechanical Engineering, Sakarya University, Sakarya, Turkiye, 54000)0000-0001-9264-9971
Pages
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Publication Date
2022-10-18
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

A common missing meteorological data-filling algorithm may be developed in order to reduce the deviations in energy analysis results.

📌 3 Key Takeaways

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Objective & Hypothesis:The most important parameter which affects the results of building energy analysis is the weather data and it can be obtained by different methods for the same location.
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Key Findings & Data:All simulations were performed using Energyplus v9.2.
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Conclusion & Impact:A common missing meteorological data-filling algorithm may be developed in order to reduce the deviations in energy analysis results.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Typical Meteorological Year · Weight Coefficients · Building Energy Analysis

Abstract

The most important parameter which affects the results of building energy analysis is the weather data and it can be obtained by different methods for the same location. Although lots of studies have been conducted for Türkiye, it was seen that the impact of different weather data for the same location has never been investigated. The aims of this study were to compare the heating and cooling demands of the buildings with respect to different weather files. Building loads were calculated using five different meteorological source data. Calculations are made for eight cities which represent heating and cooling dominated climates of Türkiye. Calculation procedure of internal heat gain was explained in detail. All simulations were performed using Energyplus v9.2. The findings of the comparison showed that although some results are similar to each other for some weather files, they could have great variances in the energy analysis also. A common missing meteorological data-filling algorithm may be developed in order to reduce the deviations in energy analysis results.

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Cite This Article

Acar, U., Kaşk, Ö., Tokgöz, N. (2022). The effects of different typical meteorological year data on the heating and cooling demand of buildings: Case study of Turkiye. Journal of Thermal Engineering, Volume: 8 Issue: 5. https://doi.org/10.18186/thermal.1191087

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