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How combination of control methods and renewable energies leads a large commercial building to a zero-emission zone – A case study in U.S

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  • Esmaeilzadeh, Ahmad
  • Deal, Brian
  • Yousefi-Koma, Aghil
  • Zakerzadeh, Mohammad Reza

Abstract

This paper aims to develop a decision-making tool to minimize large commercial buildings’ Heating, Ventilation, Air-conditioning, and Cooling (HVAC) system environmental footprints. We modeled a terminal of an airport as a case study constituting hot water boilers, chillers, and air handling units, which forms the initial HVAC system, in EnergyPlus. The case study model is validated with monthly energy consumption data. Then, the decision-making system is applied on the retrofitted hybrid HVAC system resulted by combining Building Integrated Photovoltaic (BIPV) system, Combined Cooling, Heating and Power (CCHP) unit, and existing HVAC system. The decision-making system is developed based on three kinds of optimized controllers including Model Predictive Controller (MPC), Fuzzy Sliding Mode Control (FSMC), and relay controller (Initial controller of HVAC system). The optimization is designed based on reducing CO2 emission as well as providing comfort temperature. We found that retrofitting by hybrid system reduces emission by 90% compared with the initial system and applying intelligent controllers including MPC and FSMC, improve it to 95% CO2 emission reduction. While initial system provides comfort temperature 85% of the simulation period, retrofitted HVAC system controlled by MPC or FSMC sets indoor temperature 96% of 1-year simulation.

Suggested Citation

  • Esmaeilzadeh, Ahmad & Deal, Brian & Yousefi-Koma, Aghil & Zakerzadeh, Mohammad Reza, 2023. "How combination of control methods and renewable energies leads a large commercial building to a zero-emission zone – A case study in U.S," Energy, Elsevier, vol. 263(PD).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pd:s0360544222028304
    DOI: 10.1016/j.energy.2022.125944
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    3. Gao, Yuan & Hu, Zehuan & Chen, Wei-An & Liu, Mingzhe, 2024. "Solutions to the insufficiency of label data in renewable energy forecasting: A comparative and integrative analysis of domain adaptation and fine-tuning," Energy, Elsevier, vol. 302(C).

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