Optimization of Design Parameters for Office Buildings with Climatic Adaptability Based on Energy Demand and Thermal Comfort

Yuang Guo and Dewancker Bart
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Yuang Guo: Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan
Dewancker Bart: Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan

Sustainability, 2020, vol. 12, issue 9, 1-23

Abstract: According to a Chinese building energy demand report of 2016, building consumption is accelerating at a spectacular rate, especially for urban public buildings. In this study, various design parameters that meet the principle of climate adaptation are proposed to achieve the unity of energy utilization and indoor thermal comfort level. According to the local energy conservation codes, five typical benchmark geometric models were established in Open Studio (Sketch-Up plug-in) for sites representative of various climates, meanwhile, adopting the engine of Energy Plus (EP-Launch) to calculate the instrument definition file (IDF), respectively, for assessing the coupling relationship between energy consumption as well as thermal comfort. Results implied that based on the time proportion (8760 h) that met the level 1 comfort range, total energy reductions of different Chinese climate regions were different. Among them, the severe cold zone (SCZ—Changchun) and hot summer and cold winter zone (HSCW—Shanghai) appeared to have the greatest energy saving potential with 18–24% and 16–19%, respectively, while the cold zone (CZ—Beijing) and mild zone (MZ—Kunming) approximately equaled 15% and 12–15%, and the saving space of the hot summer and warm winter zone (HSWW—Haikou) appeared relatively low, only around 5–7%. Although the simulation results may be limited by the number of parameter settings, the main ones are under consideration seriously, which is further indication that there is still much room for appropriate improvements in the local public building energy efficiency codes.

Keywords: numerical simulation; parametric optimization; energy demand; thermal comfort; office buildings; Chinese climate region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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