Evolutionary algorithms on reducing energy consumption in buildings: an approach to provide smart and efficiency choices, considering the rebound effect

Ricardo S. Santos, J. C. O. Matias, António Abreu, Francisco Reis

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

This paper presents a model to promote energy efficiency among household appliances, by supporting the consumer decisions through the maximization of his savings, associated to a set of electrical appliances from the market to be acquired. Not always an efficient equipment from the market, is more expensive than a less efficient one, which can lead the consumer to compromise the expected savings on future. Given the several models/brands available on market and its possible combinations, the problem can be defined as a combinatorial problem, whose complexity can compromise the efficiency of using deterministic algorithms. Genetic algorithms (GAs) were therefore included in the model, whose results were compared later with Simplex to verify the quality of the obtained solutions, as well as their performance. In addition, it was performed a statistical analysis of the obtained results, as well as a sensitivity analysis of GAs parameters, to validate their robustness. we conclude that the proposed method can provide several efficient solutions to the problem, as well as sensitize the consumer to their choices made on future, by estimating their corresponding rebound effect.

Original languageEnglish
Pages (from-to)729-755
Number of pages27
JournalComputers and Industrial Engineering
Volume126
DOIs
Publication statusPublished - 1 Dec 2018

Keywords

  • Energy efficiency
  • Genetic algorithms (GAs)
  • Indirect Rebound Effect
  • Life Cycle Cost Analysis (LCCA)
  • Simplex method

UN Sustainable Development Goals (SDGs)

  • SDG 12 - Responsible Production and Consumption

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