Optimization of Intelligent Heating Ventilation Air Conditioning System in Urban Building based on BIM and Artificial Intelligence Technology

Zhonghui Liu1 and Gongyi Jiang2

  1. School of Environmental Engineering, the University of Kitakyushu
    Kitakyushu 8080135, Japan
    z8dbb412@eng.kitakyu-u.ac.jp
  2. Tourism College of Zhejiang
    Hangzhou 310000, China
    jgy1128@tourzj.edu.cn

Abstract

The study aims to effectively reduce building energy consumption, improve the utilization efficiency of building resources, reduce the emission of pollutants and greenhouse gases, and protect the ecological environment. A prediction model of heating ventilation air conditioning (HVAC) energy consumption is established by using back propagation neural network (BPNN) and adapted boosting (Adaboost) algorithm. Then, the HVAC system is optimized by building information modeling (BIM). Finally, the effectiveness of the urban intelligent HVAC optimization prediction model based on BIM and artificial intelligence (AI) is further verified by simulation experiments. The research shows that the error of the prediction model is reduced, the accuracy is higher after the Adaboost algorithm is added to BPNN, and the average prediction accuracy is 86%. When the BIM is combined with the prediction model, the HVAC programme of hybrid cooling beam + variable air volume reheating is taken as the optimal programme of HVAC system. The power consumption and gas consumption of the programme are the least, and the CO 2 emission is also the lowest. Programme 1 is compared with programme 3, and the cost is saved by 37% and 15%, respectively. Through the combination of BIM technology and AI technology, the energy consumption of HVAC is effectively reduced, and the resource utilization rate is significantly improved, which can provide theoretical basis for the research of energy-saving equipment.

Key words

building information modeling, Adaboost-BP algorithm, heating ventilation air conditioning system, energy consumption prediction, simulation

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS200901027L

Publication information

Volume 18, Issue 4 (September 2021)
Year of Publication: 2021
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Liu, Z., Jiang, G.: Optimization of Intelligent Heating Ventilation Air Conditioning System in Urban Building based on BIM and Artificial Intelligence Technology. Computer Science and Information Systems, Vol. 18, No. 4, 1379–1394. (2021), https://doi.org/10.2298/CSIS200901027L