Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort: Paper No. 022043

C. Turley, M. Jacoby, Gregor Henze, G. Pavlak

Research output: Contribution to conferencePaper

1 Scopus Citations


The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.
Original languageAmerican English
Number of pages8
StatePublished - 2020
EventWorld Sustainable Built Environment Conference - Beyond 2020 - Gothenburg, Sweden
Duration: 2 Nov 20204 Nov 2020


ConferenceWorld Sustainable Built Environment Conference - Beyond 2020
CityGothenburg, Sweden

NREL Publication Number

  • NREL/CP-5500-78726


  • energy utilization
  • forecasting
  • housing
  • model predictive control
  • predictive analytics
  • predictive control systems
  • sustainable development
  • thermal comfort


Dive into the research topics of 'Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort: Paper No. 022043'. Together they form a unique fingerprint.

Cite this