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Predictive control for indoor environment based on thermal adaptation.

Xinyin Xu1, Baochuan Fu1, Zhengtian Wu1

  • 1School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu, China.

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|April 19, 2021
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Summary
This summary is machine-generated.

This study introduces a model predictive control (MPC) strategy to optimize indoor environmental quality (IEQ) by anticipating changes and adapting to human thermal comfort. This approach saves energy by reducing air-conditioning and lighting usage.

Keywords:
Indoor environment qualitybilinear modelmodel predictive controlthermal adaptation

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Area of Science:

  • Building Science
  • Environmental Engineering
  • Human Comfort Studies

Background:

  • Indoor environmental quality (IEQ) significantly impacts occupant health and comfort.
  • Predictive control of IEQ is crucial for energy efficiency and well-being.
  • Human thermal adaptation influences comfort and energy consumption.

Purpose of the Study:

  • To develop a predictive model for indoor environmental parameters.
  • To implement a model predictive control (MPC) strategy for IEQ management.
  • To integrate human thermal adaptation into the control system for enhanced comfort and energy savings.

Main Methods:

  • Established an office building model incorporating HVAC and lighting systems using simulation and mathematical methods.
  • Constructed a bilinear model linking IEQ parameters with control variables.
  • Identified unknown parameters through experimental validation.
  • Developed an MPC strategy considering dynamic neutral temperature based on outdoor and indoor temperatures.

Main Results:

  • The control system successfully adjusted temperature setpoints based on human adaptability.
  • Air-conditioning, fan, and lighting systems were effectively managed by the MPC.
  • Demonstrated a reduction in the operational time for air-conditioning and lighting systems.

Conclusions:

  • The proposed MPC strategy enhances indoor environmental quality by proactively managing parameters.
  • Integrating human thermal adaptation leads to significant energy savings.
  • This approach offers a viable method for optimizing building energy performance and occupant comfort.