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%0 Thesis %A Cai, Xiaoye %T Automated planning and implementation of mode-based control algorithms for building energy systems %I Rheinisch-Westfälische Technische Hochschule Aachen %V Dissertation %C Aachen %M RWTH-2025-06631 %P 1 Online-Ressource : Illustrationen %D 2025 %Z Veröffentlicht auf dem Publikationsserver der RWTH Aachen University. - Schreibfehler im Übersetzungstitel des Dokuments: Plannung %Z Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2025 %X The performance gap in the building industry, reflecting the mismatch between predicted and actual energy performance, persists despite extensive research efforts. Building Automation and Control Systems (BACS) offer a promising solution, with studies demonstrating substantial energy savings and performance improvements. However, traditional BACS planning and implementation processes face challenges, particularly in integrating renewable energy sources and ensuring efficient control function development. Manual programming and inadequate digitization of control function documentation further compound these issues, leading to suboptimal system operation and potential failures. Thus, this work contributes to this field by developing software-assisted approaches for automated planning and implementation of mode-based control algorithms for Building Energy Systems (BES). By harnessing the capabilities of the Industrial Foundation Class (IFC) for digital documentation, the developed planning tool streamlines the systematic development of mode-based control algorithms. It achieves this through automated BES decomposition, rule-based identification of operating modes, and automated modeling of BES alongside mode-based control algorithms using Modelica. Early-stage simulation-assisted evaluations ensure the appropriateness of control designs. Moreover, to bridge the gap between planning and implementation phases and mitigate information loss and ambiguity, this work pioneers an IFC-based documentation method. This approach allows for the documentation of planned control algorithms within the IFC schema, facilitating seamless integration with the implementation tool. Consequently, the planned control algorithms can be automatically extracted from IFC data and translated into Programmable Logic Controller (PLC) code, expediting the implementation process while ensuring accuracy and reliability.By applying this toolchain to two use cases, the study demonstrates its effectiveness in automating the planning and implementation of mode-based control algorithms for BES stored in IFC data. This analysis shows that the toolchain efficiently automates the extraction and processing of desired BES topologies from IFC data, facilitating the planning of mode-based control algorithms. Simulation outcomes validate the successful modeling of these planned control algorithms in Modelica, enabling their evaluation and refinement. Moreover, simulation results from the implementation phase demonstrate the seamless integration of the planned control algorithms into IFC data and their subsequent direct implementation in PLCs. In summary, this methodology significantly advances the digitization of planning and implementation of control functions in BACS. The developed toolchain is expected to be applied in practical projects in the future. %F PUB:(DE-HGF)11 %9 Dissertation / PhD Thesis %R 10.18154/RWTH-2025-06631 %U https://publications.rwth-aachen.de/record/1015904