RT info:eu-repo/semantics/doctoralThesis
T1 The use of BIM and advanced digital technologies for energy-efficient building renovation projects: a path towards digital building twins
A1 Álvarez Díaz, Sonia
A2 Universidad de Valladolid. Escuela de Doctorado
K1 Eficiencia energética
K1 Building information modelling
K1 BIM
K1 Building renovation
K1 Renovación de edificios
K1 Digital building twins
K1 Gemelo digital del edificio
K1 Energy efficiency
K1 Eficiencia energética
K1 6201 Arquitectura
AB Most of the buildings in the European Union (EU) were constructed before 1990, making them energy inefficient and resulting in poor indoor thermal and acoustic comfort. Given that buildings account for 40% of EU’s energy consumption and 36% of greenhouse gas (GHG) emissions, their renovation is crucial to achieve sustainability goals. Consequently, deep renovation projects are becoming increasingly prevalent, driven by European regulations aimed at improving energy performance and reducing environmental impacts to achieve climate neutrality by 2050. In line with the European Commission's Recommendation (EU) 2019/786, Member States are required to develop renovation strategies incorporating a cost-benefit analysis tailored to building types and climatic zones. Developing effective strategies also requires technicians to understand the building’s current condition to propose targeted thermal or acoustic improvements. However, conducting thermal diagnostics or assessing indoor acoustic comfort often requires lengthy and complex calculations, which are prone to errors when performed manually, highlighting the need for innovative and automated approaches.Key aspects defined in the European Renovation Wave Strategy, as part of the European Green Deal, include enhancing energy efficiency, reducing carbon emissions, and integrating digital tools such as Building Information Modelling (BIM) and Digital Twins (DTs) into renovation processes to ensure sustainability and promote circularity in the building sector. Nevertheless, despite the growing adoption of BIM for creating digital models of buildings and its potential to automate renovation processes by leveraging extensive data, significant challenges persist. These include interoperability issues between BIM models and tools for energy and acoustic performance evaluation, as well as the frequent exclusion of the digitisation of the building monitoring systems from such models.This thesis addresses these challenges by developing methodologies for integrating advanced digital technologies into the renovation process, with BIM serving as the central framework, to improve energy efficiency while advancing towards the integration of Digital Building Twins (DBTs). The research is structured around two key phases: (i) renovation design and (ii) digitisation of the existing building data. The proposed approaches focus on improving decision making processes for building renovation projects, specifically in energy diagnostics and acoustic assessment, and on enhancing the digitisation of building status. The digitisation of the existing data is addressed by updating BIM models with data from the existing monitoring network.Firstly, for energy diagnostics, a Machine Learning (ML) approach based on a decision tree algorithm has been employed to analyse As-Built BIM models, diagnose critical areas, and propose targeted Energy Conservation Measures (ECMs). Secondly, for acoustic assessments, an innovative Extract, Transform, and Load (ETL) solution has been developed to automate the retrieval and processing of geometric and acoustic data from BIM models, significantly enhancing the accuracy and efficiency of acoustic comfort assessments. Finally, the integration of Building Automation and Control Networks (BACN) with BIM has been achieved by automatically updating the Industry Foundation Classes (IFC) file of the building to include devices from an existing monitoring system. This integration addresses interoperability challenges and bridges the connection between Internet of Things (IoT) devices and IFC data, simplifying the process for building owners and technical users to create and manage monitoring networks directly within BIM. The connection between static (BIM-based) and dynamic data supports the transition from static BIM models to dynamic DBTs. These methodologies have been validated in various case studies, demonstrating significant reductions in processing time and increased accuracy compared to traditional manual methods. By integrating advanced digital technologies with BIM, this thesis addresses key challenges in building renovation, including data interoperability, facilitated by the IFC standard, workflow automation, improved decision-making, and the integration of building monitoring systems. These improvements contribute to more efficient and sustainable renovation practices.
YR 2025
FD 2025
LK https://uvadoc.uva.es/handle/10324/79110
UL https://uvadoc.uva.es/handle/10324/79110
LA eng
NO Escuela de Doctorado
DS UVaDOC
RD 29-oct-2025