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A simulation-based study of model predictive control in a medium-sized commercial building.

Number: pap. 3598

Author(s) : LI P., BARIC M., NARAYANAN S., et al.

Summary

This paper presents a computationally efficient model predictive control (MPC) algorithm to optimize the energy use of the heating ventilation, and air-conditioning (HVAC) system in a multi-zone building and demonstrates the benefits using whole building energy simulations. High-fidelity models are often not well suited for optimization-based controller design and implementation. In this paper, we present an MPC algorithm using data-driven models to optimize the energy consumption of a multi-zone building served by multiple air handling units (AHUs) and a central chiller plant. The simulation results show promising benefits of applying the MPC algorithm with an average energy saving of 15% for cooling season. The computational efficiency of the MPC algorithm demonstrated makes it suitable for real-time implementation planned in the near future.

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Pages: 10 p.

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Details

  • Original title: A simulation-based study of model predictive control in a medium-sized commercial building.
  • Record ID : 30006855
  • Languages: English
  • Subject: Environment
  • Source: 2012 Purdue Conferences. 2nd International High Performance Buildings Conference at Purdue.
  • Publication date: 2012/07/16

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