Semantic modelling of building energy flexibility information with solar photovoltaics into BIM environment

Abstract

The convergence of building-integrated photovoltaics (BIPV) with battery energy storage (BES) and building energy flexibility (BEF) control is progressively gaining traction in contemporary contexts. Within the operational and maintenance (O&M) frameworks of these integrated systems, a substantial corpus of knowledge and information is not only encapsulated but also generated. This accentuates a burgeoning necessity for enhanced information exchange among these interconnected systems, thereby accentuating the imperative to amalgamate a diverse spectrum of domain knowledge. Despite this imperative, these systems often operate in relative isolation during O&M procedures, thereby suffering from a deficiency in comprehensive machine-readable knowledge representation. In the contemporary era characterized by semantic web technologies, ontology-driven methodologies present a promising avenue for amalgamating and harmonizing heterogeneous information streams within these integrated systems. However, the knowledge representatives for the O&M of BIPV, BES, and BEF are still inadequate in the ontology fields. In addition, the semantic data of these systems does not interface with the building sector correspondingly. This study aims to bridge these gaps by addressing the insufficient ontology named BIPV-BES-BEF which covers the BIPV, BES, and BEF O&M domains while integrating relevant information into the Building Information Modeling (BIM) environment. The research commences with a thorough literature review encompassing recent endeavors in ontology- and BIM-based initiatives concerning BIPV, BES, and BEF. The review not only underscores the importance of ontology-driven data integration as elucidated in current literature but also delves into the methodologies of ontology construction, rule formulation, and the alignment of ontology with BIM systems. Concepts from standards were meticulously examined and distilled, and existing relevant ontologies were explained and compared. After that, semantic textual similarity techniques such as WordNet and Cosine Similarity were applied to extract and harmonize pertinent classes within existing ontologies. The intricacies of the developed BIPV-BES-BEF ontology were expounded upon, with Semantic Web Rule Language (SWRL) rules crafted for this ontology by established standards. Subsequently, an ontology implementation procedure based on a case study was executed, demonstrating the ontology's capability to deduce knowledge from input scenarios. After that, the constructed ontology was aligned with BIM Industry Foundation Classes Ontology Web Language (IfcOWL) by mapping relevant classes to IfcOWL classes, forming IfcOWL_3B. This ontology was validated in a practical case study, affirming its efficacy in knowledge inference in real-world scenarios. This study contributes substantially by integrating information concerning BIPV, BES, and BEF into a combined system, thereby establishing a connection between renewable energy technologies and BIM. Incorporating ontology into the BIM environment enhances and broadens the scope of applications for BIPV, BES, and BEF within the building sector, especially during the O&M phase.