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Development of solar heat gain factors database using meteorological data
Affiliation:1. Department of Chemical Drugs, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho 1/3, 612 42 Brno, Czech Republic;2. Department of Biological Sciences, Cork Institute of Technology, Bishopstown, Cork, Ireland;3. Department of NMR Spectroscopy and Mass Spectrometry, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinskeho 9, 812 37 Bratislava, Slovakia;4. Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho 1/3, 612 42 Brno, Czech Republic;5. Institute of Chemistry, Faculty of Natural Sciences, Comenius University, Mlynska dolina Ch-2, 842 15 Bratislava, Slovakia;1. Končar — Electrical Engineering Institute, Fallerovo šetalište 22, 10000 Zagreb, Croatia;2. University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Energy and Power Systems, Unska 3, 10000 Zagreb, Croatia;3. Končar — Electrical Industry Inc., Fallerovo šetalište 22, 10000 Zagreb, Croatia;1. Research Center of System Health Maintenance, Chongqing Technology and Business University, Chongqing 400067, China;2. Department of Mechanical Engineering, University of Ottawa, Ottawa, ON, Canada K1N 6N5
Abstract:In tropical and subtropical regions, solar heat gain via fenestration, particularly on vertical surfaces, plays an important role in determining the thermal performance of a building. For sizing air-conditioning equipment, maximum solar heat gain factors (SHGFs) are used for estimating the design peak load. Recently, the SHGF data representing the prevailing weather conditions have become essential and more practical for part load performance designs and daylighting schemes evaluation. In the absence of measured solar radiation data for the determination of SHGFs, meteorological radiation models may be used. This paper presents the validation of SHGFs prediction models based on sunshine hours and horizontal solar data. Statistical assessments for the models have shown that using sunshine hours to predict the hourly SHGFs may not be appropriate for dynamic building simulation studies. For the average SHGFs computation, all models present acceptable results. In determining the SHGFs for horizontal and vertical surfaces at the peak and other significant levels, all prediction models perform better than the ASHRAE clear sky approach, particularly at high significant levels. This finding also provides information for the estimation of total air-conditioning plant capacity at both the peak load operation and the multiple equipment sizing under part load condition.
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