Session 4B - Buildings

Title:	Detailed White-Box Non-Linear Model Predictive Control for Scalable Building HVAC Control
Authors:	Filip Jorissen, Damien Picard, Kristoff Six and Lieve Helsen
Abstract:	Grey-box and black-box MPC approaches for building HVAC applications often use lumped, low-order models with a low level of detail. While such models require smaller computation times, their accuracy is limited and there are practical constraints related to data collection, how to deal with multi-zone buildings and they often do not explicitly model the building HVAC equipment. In this paper we present an alternative approach based on detailed white-box models. TACO, a custom toolchain that builds upon physics-based Modelica models and JModelica, is used to efficiently solve the resulting optimisation problems. This paper presents a case study model of 79 zones and OCP results for this case study are discussed, demonstrating the high potential of detailed white-box MPC.
Keywords:	Optimal control of hybrid systems, HVAC, white-box modelling, building automation, TACO, JModelica, MPC
Paper:	full paper
Bibtex:	@InProceedings{modelica.org:Jorissen:2021, title = "{Detailed White-Box Non-Linear Model Predictive Control for Scalable Building HVAC Control}", author = {Filip Jorissen and Damien Picard and Kristoff Six and Lieve Helsen}, pages = {315--323}, doi = {10.3384/ecp21181315}, booktitle = {Proceedings of the 14th International Modelica Conference}, location = {Link\"oping, Sweden}, editor = {Martin Sj\"olund and Lena Buffoni and Adrian Pop and Lennart Ochel}, isbn = {978-91-7929-027-6}, issn = {1650-3740}, month = sep, series = {Link\"oping Electronic Conference Proceedings}, number = {181}, publisher = {Modelica Association and Link\"oping University Electronic Press}, year = {2021} }

Title:	Software Architecture and Implementation of Modelica Buildings Library Coupling for Spawn of EnergyPlus
Authors:	Michael Wetter, Kyle Benne and Baptiste Ravache
Abstract:	Spawn of EnergyPlus is a next-generation energy simulation engine that targets control design and implementation workflows. Spawn reuses the weather, lighting, loads, and envelope modules from EnergyPlus implemented in C++. It couples these with HVAC and control models implemented in Modelica. Spawn has been designed to perform coupled simulation with any number of EnergyPlus envelope models, supporting simulation of a single building or multiple buildings as part of a district energy system. This paper describes how these Modelica objects are implemented and synchronized to allow the modular specification at the Modelica-level that uses a shared Functional Mockup Unit (FMU) for envelope simulation. A key feature of our implementation is that multiple instances of Modelica models call C functions, which jointly build a data structure that defines the configuration of the whole building model. This data structure is then used to generate a FMU that contains a fully configured EnergyPlus model. This FMU is then accessed by all these Modelica models to exchange with EnergyPlus values for parameters, inputs and outputs during the simulation. This setup allows the Modelica models to be instantiated in a modular, object-oriented manner, as is typical for Modelica, yet they jointly construct and use a shared building model. When compared to a native Modelica building envelope simulation of comparable level of detail, the coupled Modelica-EnergyPlus model translates about 35% faster and simulates about 50% faster.
Keywords:	Modelica Buildings Library, Spawn of EnergyPlus, Modelica External Object
Paper:	full paper
Bibtex:	@InProceedings{modelica.org:Wetter:2021, title = "{Software Architecture and Implementation of Modelica Buildings Library Coupling for Spawn of EnergyPlus}", author = {Michael Wetter and Kyle Benne and Baptiste Ravache}, pages = {325--334}, doi = {10.3384/ecp21181325}, booktitle = {Proceedings of the 14th International Modelica Conference}, location = {Link\"oping, Sweden}, editor = {Martin Sj\"olund and Lena Buffoni and Adrian Pop and Lennart Ochel}, isbn = {978-91-7929-027-6}, issn = {1650-3740}, month = sep, series = {Link\"oping Electronic Conference Proceedings}, number = {181}, publisher = {Modelica Association and Link\"oping University Electronic Press}, year = {2021} }

Title:	Coupling physical and machine learning models: case study of a single-family house
Authors:	Basak Falay, Sandra Wilfling, Qamar Alfalouji, Johannes Exenberger, Thomas Schranz, Christian Møldrup Legaard, Ingo Leusbrock and Gerald Schweiger
Abstract:	Future intelligent and integrated energy systems must have a high degree of flexibility and efficiency to ensure reliable and sustainable operation. Along with the rapid expansion of renewable energy, this degree of flexibility and efficiency can be achieved by overcoming the clear separation between different sectors and by increasing connectivity and the associated data availability through the integration of sensors and edge/fog computing \cite{vatanparvar2018}. All of these developments drive the transition from towards so-called Cyber-Physical Energy Systems . The Cyber technologies (sensors, edge/fog computing, IoT networks, etc.) are able to monitor the physical systems, to enable communication between different subsystems and to control them. The emergence of Cyber-Physical Systems poses new challenges for traditional modelling and simulation approaches.
Keywords:	co-simulation, building, smart energy system
Paper:	full paper
Bibtex:	@InProceedings{modelica.org:Falay:2021, title = "{Coupling physical and machine learning models: case study of a single-family house}", author = {Basak Falay and Sandra Wilfling and Qamar Alfalouji and Johannes Exenberger and Thomas Schranz and Christian M{\o}ldrup Legaard and Ingo Leusbrock and Gerald Schweiger}, pages = {335--341}, doi = {10.3384/ecp21181335}, booktitle = {Proceedings of the 14th International Modelica Conference}, location = {Link\"oping, Sweden}, editor = {Martin Sj\"olund and Lena Buffoni and Adrian Pop and Lennart Ochel}, isbn = {978-91-7929-027-6}, issn = {1650-3740}, month = sep, series = {Link\"oping Electronic Conference Proceedings}, number = {181}, publisher = {Modelica Association and Link\"oping University Electronic Press}, year = {2021} }

Title:	Underfloor heating system model for building performance simulations
Authors:	Stephan Göbel, Elaine Schmitt, Philipp Mehrfeld and Dirk Müller
Abstract:	The efficiency of heat pump systems is highly dependent on the temperature gap between the sink and the source side. Therefore, it is necessary to accurately model the sink side to enable the most accurate and holistic analysis of building energy systems. In both residential and non-residential buildings, underfloor heating systems are becoming more and more widely used. Their application can reduce the flow temperature of the heating system compared to a radiator and thus increase the efficiency of a heat pump system. This paper provides an underfloor heating system model including automatic parametrization according to prEN 1264-3:2020-02. Since the model represents a whole underfloor system, it consists at the system level of the distributor and several heating circuits and takes at the smallest level the heat transfer from a pipe element through different floor layers into account. The model is verified for the system requirements according to prEN 1264-2:2020-02. A parameter study with a variety of different underfloor heating parameters and floor layers shows that reductions of heat transfer in the underfloor heating system are compensated primarily by increasing the supply temperature. The highest influence on the temperature level of the system is exerted by the pipe spacing T, which raises the flow temperature by up to 10.9 K, from 36.6 °C (T = 100 mm) to 47.5 °C (T = 400 mm). The model is freely available on GitHub: https://github.com/RWTHEBC/AixLib/tree/issue890_HOMProject_FloorHeating
Keywords:	Building performance simulation, EN 1264, automatic parametrization
Paper:	full paper
Bibtex:	@InProceedings{modelica.org:Gobel:2021, title = "{Underfloor heating system model for building performance simulations}", author = {Stephan G\"obel and Elaine Schmitt and Philipp Mehrfeld and Dirk M\"uller}, pages = {343--349}, doi = {10.3384/ecp21181343}, booktitle = {Proceedings of the 14th International Modelica Conference}, location = {Link\"oping, Sweden}, editor = {Martin Sj\"olund and Lena Buffoni and Adrian Pop and Lennart Ochel}, isbn = {978-91-7929-027-6}, issn = {1650-3740}, month = sep, series = {Link\"oping Electronic Conference Proceedings}, number = {181}, publisher = {Modelica Association and Link\"oping University Electronic Press}, year = {2021} }