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Field demonstration of predictive heat pump water heater control.

Number: 3536

Author(s) : REYES PREMER L. D., SEMMELMANN L., PERGANTIS E.N., GROLL E. A., ZIVIANI D., KIRCHER K. J.

Summary

Heat pump water heaters (HPWHs) could significantly reduce energy costs and greenhouse gas emissions from water heating, the second largest energy use in residential buildings. Today, most HPWHs use electric resistance heating elements to maintain comfortable water temperatures even during large water draws. Unfortunately, heating elements
significantly decrease energy efficiency, and their current and voltage requirements may necessitate costly electrical work in older homes. This paper develops and field-tests a model predictive control (MPC) system that enables a HPWH with no heating elements to maintain comfort at high efficiency. By contrast to most prior experimental studies on water heater MPC, which often use perfectly-forecasted water draws in controlled laboratory settings, this paper reports field tests from a real home with three full-time occupants. The occupants’ water draws are forecasted using a machine learning model and a scalable training methodology. This paper also presents occupant feedback on thermal comfort, as well as an Internet of Things infrastructure that enables real-time data acquisition and control. In the MPC formulation, the energy savings were 11% with the same thermal comfort as the manufacturer’s constant set-point control. An adjusted MPC formulation substantially improved thermal comfort while modestly increasing energy costs.

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Pages: 10 p.

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Details

  • Original title: Field demonstration of predictive heat pump water heater control.
  • Record ID : 30032915
  • Languages: English
  • Subject: Technology
  • Source: 2024 Purdue Conferences. 8th International High Performance Buildings Conference at Purdue.
  • Publication date: 2024/07/15

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