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

被引:0
|
作者
Acar, Ugur [1 ]
Kask, Onder [2 ]
Tokgoz, Nehir [3 ]
机构
[1] Republ Turkey Minist Environm & Urbanizat, Prov Directorate Osmaniye, TR-80000 Osmaniye, Turkiye
[2] Osmaniye Korkut Ata Univ, Dept Mech Engn, TR-80000 Osmaniye, Turkiye
[3] Sakarya Univ, Dept Mech Engn, TR-54000 Sakarya, Turkiye
来源
JOURNAL OF THERMAL ENGINEERING | 2022年 / 8卷 / 05期
关键词
Typical Meteorological Year; Weight Coefficients; Building Energy Analysis; Turkiye; DIFFERENT CLIMATES; GENERATION;
D O I
10.18186/thermal.1191087
中图分类号
O414.1 [热力学];
学科分类号
摘要
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 Turkiye, 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 Turkiye. 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.
引用
收藏
页码:667 / 680
页数:14
相关论文
共 50 条
  • [1] The efficiency of a typical meteorological year and actual climatic data in the analysis of energy demand in buildings
    Grudzinska, Magdalena
    Jakusik, Ewa
    BUILDING SERVICES ENGINEERING RESEARCH & TECHNOLOGY, 2015, 36 (06): : 658 - 669
  • [2] A climate analysis tool for passive heating and cooling strategies in hot humid climate based on Typical Meteorological Year data sets
    Nguyen, Anh-Tuan
    Reiter, Sigrid
    ENERGY AND BUILDINGS, 2014, 68 : 756 - 763
  • [3] Analysis of Daily Energy Demand for Cooling in Buildings with Different Comfort Categories-Case Study
    Csaky, Imre
    ENERGIES, 2021, 14 (15)
  • [4] Comparison of different methods for generating Typical Meteorological Year in air cooling system design from different environment
    Hu L.
    Li Z.
    He X.
    Zhu B.
    Cao H.
    Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering, 2010, 18 (04): : 539 - 547
  • [5] Generation and application of typical meteorological year data for PV system potential assessment: A case study in China
    Yu, Ying
    Chou, Jinshuai
    Yao, Xing
    Ma, Nana
    JOURNAL OF BUILDING ENGINEERING, 2024, 86
  • [6] Integrating phase change materials in buildings for heating and cooling demand reduction - A global study
    Mettrick, Andrew James
    Ma, Zhiwei
    CASE STUDIES IN THERMAL ENGINEERING, 2024, 63
  • [7] The performance of shallow GSHP in buildings for heating and cooling: A case study in Jordan
    Kiwan S.
    Rawashdeh O.
    Alawawdeh N.
    Alkhalidi A.
    International Journal of Thermofluids, 2023, 19
  • [8] An agile heating and cooling energy demand model for residential buildings. Case study in a mediterranean city residential sector
    Prades-Gil, C.
    Viana-Fons, J. D.
    Masip, X.
    Cazorla-Marin, A.
    Gomez-Navarro, T.
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2023, 175
  • [9] Data-driven short-term load forecasting for heating and cooling demand in office buildings
    Ashouri, Araz
    Shi, Zixiao
    Gunay, H. Burak
    CLIMATE RESILIENT CITIES - ENERGY EFFICIENCY & RENEWABLES IN THE DIGITAL ERA (CISBAT 2019), 2019, 1343
  • [10] A Case Study of Air Infiltration for Highly Airtight Buildings under the Typical Meteorological Conditions of China
    Du, Yichen
    Ji, Yongming
    Duanmu, Lin
    Hu, Songtao
    BUILDINGS, 2024, 14 (06)