Towards a Digital Representation of Building Systems Controls

Authors

DOI:

https://doi.org/10.52825/isec.v1i.1217

Keywords:

Building Information Modeling (BIM), Building Automation Systems (BAS), Semantic Web Technologies (SWT), Programmable Logic Controller (PLC), Digitization

Abstract

Energy monitoring and performance optimization processes play a significant role in ensuring energy-efficient building operation. However, the current implementation of these processes requires substantial time and effort due to the fragmented and non-digital nature of technical building equipment information. To address these challenges, we demonstrate the application of the PLCont methodology within an ongoing monitoring process in a real building. PLCont utilizes Semantic Web Technologies and established RDF ontologies to describe the control topology. The digital representation of control functions aligns closely with the IEC standard 61131-3, and the PLCont ontology establishes a connection between the topology and the control functions. We compare the conventional approach and the PLCont methodol-ogy using the supply air temperature control of an Air Handling Unit (AHU) as a use case. A graphical user interface built upon the PLCont backend provides a comprehensive represen-tation of the system's functionality. It displays the system topology as a digital HVAC schema, the function code exported from the PLC, time-series data plots, and textual descriptions of implemented functions. We demonstrate how this approach enhances transparency and facil-itates the identification and elimination of faulty system behavior, ultimately contributing to the optimization and energy efficiency of building systems.

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References

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Published

2024-04-12

How to Cite

Ihlenburg, M., Réhault, N., Herkel, S., & Benndorf, G. (2024). Towards a Digital Representation of Building Systems Controls. International Sustainable Energy Conference - Proceedings, 1. https://doi.org/10.52825/isec.v1i.1217

Conference Proceedings Volume

Section

Solutions for Energy Efficiency

Funding data