Building-Ecofit: An Extended Framework for Residential Home Retrofitting

The absence of cohesive, technology-aware frameworks for energy-efficient building retrofits leads to inefficiencies, jeopardizing both corporate success and energy and emission reduction targets. Our end-to-end, all-stakeholder framework leverages advanced technologies, such as precise structure and performance modeling techniques, optimization and simulation methods, and digital twins, seamlessly integrated into a unified process supported by sophisticated data management. This holistic approach unleashes the synergistic technological potential throughout the retrofit project, significantly improving the inherent decision-making processes. Additionally, we introduce a conceptual collaborative digital twin ecosystem for the generation of knowledge in retrofitting and building automation systems, and pinpoint areas for further research.

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Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.09.182
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
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article

Building-Ecofit: An Extended Framework for Residential Home Retrofitting

Thomas Völling, J. David, Jakob Fiebing
IFAC-PapersOnLine
Building Energy and Comfort Optimization
article

Building-Ecofit: An Extended Framework for Residential Home Retrofitting

Thomas Völling, J. David, Jakob Fiebing
article en

Abstract

The absence of cohesive, technology-aware frameworks for energy-efficient building retrofits leads to inefficiencies, jeopardizing both corporate success and energy and emission reduction targets. Our end-to-end, all-stakeholder framework leverages advanced technologies, such as precise structure and performance modeling techniques, optimization and simulation methods, and digital twins, seamlessly integrated into a unified process supported by sophisticated data management. This holistic approach unleashes the synergistic technological potential throughout the retrofit project, significantly improving the inherent decision-making processes. Additionally, we introduce a conceptual collaborative digital twin ecosystem for the generation of knowledge in retrofitting and building automation systems, and pinpoint areas for further research.

IFAC-PapersOnLineVol. 59(10)
Technische Universität Berlin (DE)
Openalex Percentile: Top 71%
Building Energy and Comfort Optimization
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