Occupant-based energy upgrades selection for Canadian residential buildings based on field energy data and calibrated simulations

Anber Rana; Piyaruwan Perera; Rajeev Ruparathna; Hirushie Karunathilake; Kasun Hewage; M Shahria Alam; Rehan Sadiq

doi:10.1016/j.jclepro.2020.122430

Occupant-based energy upgrades selection for Canadian residential buildings based on field energy data and calibrated simulations

J Clean Prod. 2020 Oct 20:271:122430. doi: 10.1016/j.jclepro.2020.122430. Epub 2020 Jun 16.

Authors

Anber Rana¹, Piyaruwan Perera¹, Rajeev Ruparathna², Hirushie Karunathilake³, Kasun Hewage¹, M Shahria Alam¹, Rehan Sadiq¹

Affiliations

¹ School of Engineering, The University of British Columbia, Okanagan Campus, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
² Faculty of Engineering, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada.
³ Department of Mechanical Engineering, University of Moratuwa, Katubedda, Moratuwa, 10400, Sri Lanka.

Abstract

Occupant behavior in residential buildings has a direct impact on the effectiveness of energy-saving measures. In order to realize a buildings' carbon mitigation targets, the impact of individual occupancy profiles needs to be integrated with building simulation models. This paper introduces a decision support framework as a potential solution to make energy performance upgrade choices based on different occupancy profiles. This framework has been demonstrated through a case study of two single-family detached homes in Canada, which were highly instrumented with sensors for monitoring energy input and output. The case studies represented two common occupancy profiles-(1) a family of four (consisting of 2 working adults and 2 teenagers); and (2) a retired couple. Firstly, calibrated energy models were developed by using one-year energy use data collected through an intrusive load monitoring technique. Secondly, energy upgrade combinations were considered for each profile and tested for additional investment, payback period and greenhouse gas (GHG) emissions. Lastly, the most suitable combination of energy upgrade for each profile was ranked using a multi-criteria decision-making method (e.g., TOPSIS). Results indicated that the retired couple used more energy than the family of four and required energy upgrades with usually higher payback periods to achieve the same level of GHG emission reduction. The results of this research are timely for energy policymaking and developing best management practices, which need to be implemented along with the deployment of more stringent building standards and codes.

Keywords: Calibration models; Decision making; Dwelling; Energy performance upgrade; Occupancy profiles.