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Adopting smart retrofits: a decision-making model and benchmarking criteria

Author(s): ORCID

ORCID
Medium: journal article
Language(s): English
Published in: Built Environment Project and Asset Management, , n. 3, v. 14
Page(s): 366-383
DOI: 10.1108/bepam-02-2023-0034
Abstract:

Purpose

Energy consumption in existing office buildings has been growing in parallel with the rise in occupant energy demand. As a result, many building owners have given smart retrofits (SRs) a higher priority. However, the utilisation of suitable SRs from a range of SRs has become a challenging task. The purpose of this paper is to develop a decision-making model to select the most suitable SRs for conventional office buildings and form a set of benchmarks for assessing the performance of SRs.

Design/methodology/approach

A qualitative approach with six case studies was used. Content analysis was carried out using NVivo to explore the factors considered for the selection of SR techniques. A decision-making model for selecting SRs in Sri Lankan office buildings was proposed. SR performance benchmarks were developed by referring to established standards and studies done in tropical office buildings.

Findings

Out of 18 identified SRs from literature, fan cycling, ventilation control and LED luminaires have been recognised as commonly used SRs in Sri Lankan office buildings. Analysis showed that HVAC retrofits saved more energy, while lighting retrofits could be easily implemented in existing buildings. The proposed decision-making model can explore further improvements to enhance the performance of SRs.

Originality/value

The selection of SRs is a comprehensive decision-making process. Metrics were established to benchmark the performance of SRs. The proposed model offers a tool for building owners and facility managers to optimise facility operations.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1108/bepam-02-2023-0034.
  • About this
    data sheet
  • Reference-ID
    10788607
  • Published on:
    20/06/2024
  • Last updated on:
    20/06/2024
 
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