Multi-variable optimization of thermal energy efficiency retrofitting of buildings using static modelling and genetic algorithms - A case study

Research output: Contribution to journalArticlepeer-review

Abstract

The retrofitting of existing buildings is an area of research that requires development in order to overcome the 'rule of thumb' based approach currently being undertaken. Simulation-based optimization is one approach that can assist consultant engineers, architects and other professionals who undertake retrofit projects. This paper presents a degree-days simulation technique coupled with a genetic algorithms optimization procedure to propose optimal retrofit solutions. The research is applied to a recently retrofitted case-study building. A comparison between the implemented retrofit solution and the simulation-based optimal solution is included to demonstrate the applicability of the research to real-world situations. This research demonstrates the necessity to carry out analysis of a project before retrofit works commence to ensure an optimal approach is taken in accordance with the project specific criteria.

Original languageEnglish
Pages (from-to)98-107
Number of pages10
JournalBuilding and Environment
Volume75
DOIs
Publication statusPublished - May 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Degree-days simulation
  • Energy efficiency
  • Energy modelling
  • Existing building retrofitting
  • Genetic algorithms
  • Multi-variable optimization

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