A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

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Publication Details

Journal
Advanced Engineering Informatics
Published
2024-12-27
DOI
https://doi.org/10.1016/j.aei.2024.103049
Citations
7
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
1.86
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article

A semantics-driven framework to enable demand flexibility control applications in real buildings

Anand Krishnan Prakash, Donal Finn, Dimitrios Rovas, Susana Martín et al.
7 citations
Advanced Engineering Informatics
Building Energy and Comfort Optimization
1.86
article

A semantics-driven framework to enable demand flexibility control applications in real buildings

Anand Krishnan Prakash, Donal Finn, Dimitrios Rovas, Susana Martín, Fernando Pereira, Marco Pritoni, James O’Donnell, Lazlo Paul, Kyriakos Katsigarakis, Conor Shaw
article en
7 citations

Abstract

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

Advanced Engineering InformaticsVol. 64
University College Dublin (IE), Universidad de Valladolid (ES), Lawrence Berkeley National Laboratory (US), University College London (GB)
Openalex Percentile: Top 15%
Building Energy and Comfort Optimization
1.86
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