Analysis of influencing factors of future passive residential building energy consumption based on software simulation

Wenjuan Huang; Bojun Wang; Yanping Yang; Cao He

doi:10.1117/12.2635436

6 May 2022 Analysis of influencing factors of future passive residential building energy consumption based on software simulation

Wenjuan Huang, Bojun Wang, Yanping Yang, Cao He

Author Affiliations +

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 1225630 (2022) https://doi.org/10.1117/12.2635436
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

Software simulation of building energy consumption has become one of the normal means of measuring building energy consumption. This paper uses Openstudio energy simulation software to construct passive residential building models from the perspective of envelope, internal loads and air conditioning systems, and future climate change. Selecting the SRESA2 emissions scenario downscales to generate weather files for the 2050s and 2080s, forecasts future passive residential building energy consumption, and analyzes the influencing factors of passive residential energy consumption. The software simulation results show that the lighting density power and equipment power of the internal load, as well as the COP of the air conditioning system and the interior design temperature, all affect the total energy consumption of the building to varying degrees. The heat transfer coefficient of the exterior walls and the temperature of the COP air conditioning system and the interior design temperature have the greatest influence on passive residential buildings. To provide reference for strategies related to passive residential building design under future climate change.

Citation Download Citation

Wenjuan Huang, Bojun Wang, Yanping Yang, and Cao He "Analysis of influencing factors of future passive residential building energy consumption based on software simulation", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 1225630 (6 May 2022); https://doi.org/10.1117/12.2635436

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