Evidence map›Paper›PMID 32834562›Full record

ArticleJournal of cleaner production2020

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

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cleaner production, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Anber RanaSchool of Engineering, The University of British Columbia, Okanagan Campus, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
Piyaruwan PereraSchool of Engineering, The University of British Columbia, Okanagan Campus, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
Rajeev RuparathnaFaculty of Engineering, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada.
Hirushie KarunathilakeDepartment of Mechanical Engineering, University of Moratuwa, Katubedda, Moratuwa, 10400, Sri Lanka.
Kasun HewageSchool of Engineering, The University of British Columbia, Okanagan Campus, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
M Shahria AlamSchool of Engineering, The University of British Columbia, Okanagan Campus, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
Rehan SadiqSchool of Engineering, The University of British Columbia, Okanagan Campus, 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
Okanagan University College · CAUniversity of British Columbia · CAUniversity of Moratuwa · LKUniversity of Windsor · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Calibration modelsDecision makingDwellingEnergy performance upgradeOccupancy profiles

Identifiers

PMID32834562
PMCPMC7295710
OpenAlexW3035623411

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.