Maximization of the Smart Readiness Indicator of Buildings Under Budget Constraints

Tristan Emich*, Shiva Faeghi, Kunibert Lennerts

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)

Abstract

The Smart Readiness Indicator (SRI) is a method proposed by the European Commission which calls for better use of the potential of smart technologies in the building sector. The introduction of the SRI is intended to raise awareness of smart building technologies and make the added value more available for building users, owners, and providers of smart services. The technological smart readiness of buildings can be determined with the SRI assessment method. The method has 54 questions, which are divided into nine domains: heating, domestic hot water, cooling, ventilation, lighting, electricity, electric vehicles, dynamic envelope and monitoring & control. Each question is assessed with up to five different levels, representing incremental levels of technological equipment. These questions form the basis for the calculation of the SRI score. When improving the SRI score of a building, to choose the technologies that will provide the maximum SRI score improvement with a limited budget can be challenging. Therefore, the aim of this paper is to help the decision makers to come up with the correct choices that have the highest impact on the SRI score. The chosen solution method here is a specific non-dominated sorting genetic algorithm (NSGA II) algorithm. The proposed method is then applied to a hypothetical building to demonstrate its applicability and capability. The results show which SRI domains and questions to focus on. This gives future directions regarding choosing technologies to be implemented.

Original languageEnglish
Title of host publicationOperations Research Proceedings 2022
Subtitle of host publicationSelected Papers of the Annual International Conference of the German Operations Research Society (GOR), Karlsruhe, Germany, September 6-9, 2022
EditorsOliver Grothe, Stefan Nickel, Steffen Rebennack, Oliver Stein
Place of PublicationCham, Switzerland
PublisherSpringer
Chapter32
Pages261-269
Number of pages9
ISBN (Electronic)978-3-031-24907-5
ISBN (Print)978-3-031-24906-8
DOIs
Publication statusE-pub ahead of print/First online - 30 Aug 2023
Externally publishedYes

Publication series

NameLecture Notes in Operations Research
VolumePart F3789
ISSN (Print)2731-040X
ISSN (Electronic)2731-0418

Keywords

  • 2025 OA procedure
  • Decision support systems
  • Energy policy and planning
  • Combinatorial optimization

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