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This study developed a rapid building modeling tool, AutoBPS-BIM, to transfer the building information model (BIM) to the building energy model (BEM) for load calculation and chiller design optimization. An eight-storey office building in Beijing, 33.2 m high, 67.2 m long and 50.4 m wide, was selected as a case study building. First, a module was developed to transfer BIM in IFC format into BEM in EnergyPlus. Variable air volume systems were selected for the air system, while water-cooled chillers and boilers were used for the central plant. The EnergyPlus model calculated the heating and cooling loads for each space as well as the energy consumption of the central plant. Moreover, a chiller optimization module was developed to select the optimal chiller design for minimizing energy consumption while maintaining thermal comfort. Fifteen available chillers were included, with capacities ranging from 471 kW to 1329 kW. The results showed that the cooling loads of the spaces ranged from 33 to 100 W/m2 with a median of 45 W/m2, and the heating load ranged from 37 to 70 W/m2 with a median of 52 W/m2. The central plant’s total cooling load under variable air volume systems was 1400 kW. Compared with the static load calculation method, the dynamic method reduced 33% of the chiller design capacity. When two chillers were used, different chiller combinations’ annual cooling energy consumption ranged from 10.41 to 11.88, averaging 11.12 kWh/m2. The lowest energy consumption was 10.41 kWh/m2 when two chillers with 538 kW and 1076 kW each were selected. Selecting the proper chiller number with different capacities was critical to achieving lower energy consumption, which achieved 12.6% cooling system energy consumption reduction for the case study building. This study demonstrated that AutoBPS-BIM has a large potential in modeling BEM and optimizing chiller design.

Publication history
Copyright
Acknowledgements

Publication history

Received: 28 November 2022
Revised: 31 January 2023
Accepted: 14 February 2023
Published: 19 April 2023
Issue date: July 2023

Copyright

© Tsinghua University Press 2023

Acknowledgements

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 51908204).

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