Simulation, implementation and monitoring of heat pump load shifting using a predictive controller

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15 Citations (Scopus)

Abstract

A predictive load shifting controller has been developed and deployed in a low-carbon house near Glasgow, UK. The house features an under floor heating system, fed by an air-source heat pump. Based on forecast air temperatures and solar radiation levels, the controller 1) predicts the following day’s heating requirements to achieve thermal comfort 2) runs heat pump during off peak periods to deliver the required heat by pre-charging the under floor heating. Prior to its installation in the building, the controller’s operating characteristics were identified using a calibrated building simulation model. The performance of the controller in the house was monitored over four weeks in 2015. The monitored data indicated that the actual thermal performance of the predictive controller was better than that projected using simulation, with better levels of thermal comfort achieved. Indoor air temperatures were between 18°C to 23°C for around 87% of the time between 07:00-22:00. However, the performance of the heat pump under load shift control was extremely poor, with the heat being delivered primarily by the unit’s auxiliary immersion coil. The paper concludes with a refined version of the controller that should improve the day-ahead energy predictions and offer greater flexibility in heat pump operation for future field trials.
LanguageEnglish
Pages890-903
Number of pages14
JournalEnergy Conversion and Management
Volume150
Early online date9 May 2017
DOIs
Publication statusPublished - 15 Oct 2017

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Pumps
Controllers
Monitoring
Thermal comfort
Heating
Air source heat pumps
Air
Solar radiation
Hot Temperature
Temperature
Carbon

Keywords

  • heat pump
  • load shifting
  • field trial
  • building simulation
  • predictive control

Cite this

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title = "Simulation, implementation and monitoring of heat pump load shifting using a predictive controller",
abstract = "A predictive load shifting controller has been developed and deployed in a low-carbon house near Glasgow, UK. The house features an under floor heating system, fed by an air-source heat pump. Based on forecast air temperatures and solar radiation levels, the controller 1) predicts the following day’s heating requirements to achieve thermal comfort 2) runs heat pump during off peak periods to deliver the required heat by pre-charging the under floor heating. Prior to its installation in the building, the controller’s operating characteristics were identified using a calibrated building simulation model. The performance of the controller in the house was monitored over four weeks in 2015. The monitored data indicated that the actual thermal performance of the predictive controller was better than that projected using simulation, with better levels of thermal comfort achieved. Indoor air temperatures were between 18°C to 23°C for around 87{\%} of the time between 07:00-22:00. However, the performance of the heat pump under load shift control was extremely poor, with the heat being delivered primarily by the unit’s auxiliary immersion coil. The paper concludes with a refined version of the controller that should improve the day-ahead energy predictions and offer greater flexibility in heat pump operation for future field trials.",
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author = "John Allison and Andrew Cowie and Stuart Galloway and Jon Hand and Nicolas Kelly and Bruce Stephen",
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AU - Galloway, Stuart

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AB - A predictive load shifting controller has been developed and deployed in a low-carbon house near Glasgow, UK. The house features an under floor heating system, fed by an air-source heat pump. Based on forecast air temperatures and solar radiation levels, the controller 1) predicts the following day’s heating requirements to achieve thermal comfort 2) runs heat pump during off peak periods to deliver the required heat by pre-charging the under floor heating. Prior to its installation in the building, the controller’s operating characteristics were identified using a calibrated building simulation model. The performance of the controller in the house was monitored over four weeks in 2015. The monitored data indicated that the actual thermal performance of the predictive controller was better than that projected using simulation, with better levels of thermal comfort achieved. Indoor air temperatures were between 18°C to 23°C for around 87% of the time between 07:00-22:00. However, the performance of the heat pump under load shift control was extremely poor, with the heat being delivered primarily by the unit’s auxiliary immersion coil. The paper concludes with a refined version of the controller that should improve the day-ahead energy predictions and offer greater flexibility in heat pump operation for future field trials.

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KW - field trial

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