Search

Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2022; Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen, Diagramme (2022). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2022, Driven by the digitalization of the construction industry as well as the expanding integration of regenerative energy systems in building technology, and the increasing use as a verification method, thermal building simulation is gaining in importance. In combination with simulations of thermo-fluid dynamics, buildings can be designed more economically and ecologically while ensuring thermal comfort. To an increasing extent, simulations are integrated into Building Information Modeling. In the context of openBIM, this includes the exchange of information using IFC files, which ideally contain a comprehensive data set for the creation of the simulation models. However, in practice, the data is often erroneous and incomplete. Consequently, the advantage of semi-automated model creation leading to a reduction in effort and increased use of simulations is lost. This also affects Space Boundary models, which are relevant for creating simulation geometries. Therefore, various methods for their downstream generation have been proposed, most notably in thermal building simulations. Disadvantages of these methods are, to varying degrees, the high demands on data quality, limitations in the accepted scenarios, and the insufficient attribution of the Space Boundaries. In addition, the requirements of Computational Fluid Dynamics are mostly not considered, although the coupled simulation can significantly increase the quality of the results. Concerning fluid dynamics simulation, only a few approaches for automated transfer of IFC data have been presented already. Existing methods often represent the building geometry in a simplified way or ignore the handling of faulty models. This thesis deals with a new method for the automated generation of Space Boundaries (IFC2SB). It is characterized by high robustness concerning model quality and comprehensive consideration of simulation- and scheme-specific requirements. In two introductory chapters, the thesis presents the state of the art in building simulation, Building Information Modeling, and Space Boundaries. Subsequently, the challenges and opportunities of existing approaches are discussed. Based on this, the new methodology IFC2SB is designed. It provides a variety of geometric and topological algorithms. Using example models and a prototypical implementation in the \CC programming language, the validity, robustness, and performance of the method are proven. Finally, the findings are discussed critically. Also, corresponding limitations, as well as potential research topics, are pointed out., Published by RWTH Aachen University, Aachen

Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2020; Aachen 1 Online-Ressource (ix, 238 Seiten) : Illustrationen, Diagramme (2020). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2020, The present work describes an auto-adaptive predictive model for quantifying simultaneity effects within load distributions of urban energy systems named AMSA (Auto-adaptive Model for Simultaneity Analysis). The mathematical structure of AMSA is based on Machine Learning techniques in combination with methods related to energy data analysis enabling the integration in intelligent interconnected energy information systems. AMSA is implemented in Matlab using a modular design including different functional components. Thus, individual modifications of interface functions and modular extensions do not influence the numerical calculation core. Previous simultaneity factor quantification for economically optimized dimensioning of energy generation plants and networks is based on experience values and empirical analysis focusing on historical measurement data. Conventional derivations of characteristic curves using measurement databases imply a decreasing simultaneity factor in combination with increasing building group sizes, which isused for replanning energy supply systems. In order to optimize the latter, it is necessary to know historical and current as well as scenario based future energy demand of single buildings and building groups taking uncertainty into account. Moreover, similarity analysis concerning building load profiles is required to recognise simultaneously recurring patterns in order to identify energy network systems. In this context, the developed model serves for knowledge gain from varying complex databases to identify decision ranges for long- and medium-term planning regarding the development of districts and urban regions. Furthermore, on operational level, it improves short-term load management strategies concerning energy supply. The derivation of suitable methods for component model development is based on appropriate scientific literature research and analysis regarding method categories with their specific characteristics as well as findings from application-based studies. An ensemble model serves to calculate future load conditions, consisting oft wore current neural networks of various depth and two support vector machine configurations using different kernels. According to input data characteristics, a building-specific suitable prediction method is automatically chosen based on an error evaluation during the method testing period. In order to analyse influences of varying weather conditions and building retrofits on simultaneity effects within urban load distributions, mathematical-statistical methods for load profile modifications are introduced. For pattern recognition of load distributions, self organizing maps combined with learning vector quantification are used, which is assigned to competitive neural networks category. In this regard, initially, buildings are automatically grouped according to their characteristic load profile. Secondly, the building group is identified, which provides the most correlated load profile compared to the district load profile. Subsequently, simultaneity factors and peak load shares of buildings an building groups are calculated. In the final part of this work, monitoring data of building-specific heating and cooling consumption of a research campus serve for model demonstration. In this context, besides statistical analysis of the database, results of preliminary studies concerning component models are presented. These include clustering of thermal load profiles, a detailed comparison concerning prediction models used as well as long-term heating load predictions based on retrofit scenarios. Furthermore, conventionally derived curves for simultaneity factors enable classification and evaluation of the results using AMSA. Taking the corporate model level into consideration, various model-related advantages may be shown: Regarding short-term load management, less generating capacities have to be provided. Regarding similarity-based grouping, key buildings and the building group may be identified, where temporal peak load shifting contains the largest share of the expected peak load on district level. This information enables predictive loading and unloading strategies for storage systems in terms of demand side management. With respect to longer-term planning periods, it is shown that simultaneity factors combined with similarity-based building classification suit for the identification of possible energy network systems. Future weather and retrofit scenario analysis demonstrates external influences on the results of simultaneity analysis, which emphasizes the demand for an auto-adaptive predictive model. The scope of future research work should focus on the validation of AMSA taking detailed information bases into account, Published by Aachen

This thesis presents a methodology and a software framework for dynamic modeling and heat demand calculations of building stocks using basic input data. Such heat demands build the foundation for the investigation of innovative efficiency measures, such as advanced control concepts and optimal design of heat supply systems. The methodology includes simplified dynamic building performance models that fulfil the requirements regarding computational effort and model complexity on urban scale. An accompanying model parameterization routine on the basis of accessible input data allows the efficient simulation of entire building stocks. Both parts, parameterization and modelling, are embedded in a workflow automation process and implemented using the programming language Python and the modelling language Modelica, respectively. The parameterization makes use of archetypes for residential buildings, offices and institute buildings, which allows for statistical enrichment of individual datasets for the given building types. The archetype for institute buildings is developed based on statistical analyses of two research centers. The simplified building performance models are based on a reduced thermal network model, which is described in the German Guideline VDI 6007-1 (2015). As part of a characterization of different model types, the use of a second order model including two state variables proves to be the best choice concerning efficiency and complexity. This model uses of one state variable each for interior and exterior building elements in addition to one separate resistance for windows.The investigations of three use cases show the framework’s ability to simulate entire building stocks using only basic input data. The use case of one of the studied research centers results in differences between simulation and measurement of less than 3% in the annual heat demand of all buildings. The simulation can in addition capture the dynamic behavior of the heat demand, what is highlighted by a coefficient of determination of 0,894. All parts of the methodology comply with the requirements regarding verification, accuracy, transparency, stability and flexibility. They can contribute to the field of urban energy modelling, if the individual application allows the use of archetypes and reduced order models. The parameterization is implemented in the Python library TEASER, the reduced order building models are integrated into the Modelica library AixLib. Both libraries are available open source at https://github.com/RWTH-EBC/TEASER and https://github.com/RWTH-EBC/AixLib.

In Forschung und Entwicklung wird die Modellierung von technischen Systemen als Ergänzung oder als Ersatz für klassische Prototypen verwendet. Die Simulation ist die Ausführung eines solchen Softwaremodells. Es entstehen Simulationsdaten, die abhängig von der Qualität des Modells Rückschlüsse auf das Originalsystem zulassen. Im Kern besteht ein hier betrachtetes Modell aus einem differential-algebraischen Gleichungssystem, das durch sogenannte Solver zeitschrittweise gelöst wird. Für die Entwicklung komplexer Modelle werden Beschreibungstechniken aus der Objektorientierung angewendet. Objekte werden in der Modellierung Komponenten genannt und fassen ein wiederverwendbares Verhalten durch Gleichungen zusammen. Ein Simulationsmodell wird werkzeugunterstützt aus Komponenten zusammengestellt, wodurch vom Gleichungssystem abstrahiert wird. Ein solches Modell durchläuft vor der Simulation einen Übersetzungsprozess, der die Hierarchie auflöst, um das Gleichungssystem zu bilden. Durch die abstrakte Beschreibungstechnik erreicht das entstehende Gleichungssystem schnell ein Größe, die einen erheblichen Berechnungsaufwand für die Simulation mit sich bringt. Aktuelle Simulationswerkzeuge nutzen während der Simulation ein festes und optimiertes Gleichungssystem, wodurch die Möglichkeiten eingeschränkt sind, grundlegende Veränderungen während der Simulation durchzuführen. Das Konzept der Strukturvariabilität behandelt Veränderungen des Gleichungssystems und bietet damit die Möglichkeit, Verhaltensänderungen oder eine Anpassung der Genauigkeit zur Effizienzsteigerung durchzuführen. Es existieren verschiedene Auslegungen und prototypische Realisierungen, die zum Teil eine eigene Modellierungssprache einführen oder Strukturvariabilität durch eine Simulationssequenz von manuell generierten, klassischen Modellen realisieren. Bisher kaum betrachtet wurde die Fragestellung, wie die unterschiedlichen Gleichungssysteme effzient beschrieben und Veränderungen ausgeführt werden können. Daher wird in dieser Arbeit gezeigt, wie Strukturvariabilität auf dem gleichen Abstraktionslevel wie das komponentenorientierte Modell beschrieben und wie die Entwicklung eines solchen Modells stattfinden kann. Dazu werden ein Vorgehensmodell und eine Notation eingeführt, die in einer Entwicklungsmethode zusammengefasst und von einem prototypischen Java-Werkzeug unterstützt werden. Die Objektorientierung der Modellierungssprache Modelica wird verwendet, um Strukturvariabilität basierend auf dem Austausch von Komponenten zur Simulationszeit zu ermöglichen. Die Methode basiert auf der Erweiterung eines klassischen Modelica-Modells um strukturvariables Verhalten. Das Vorgehensmodell zeigt, in welcher Reihenfolge und mit welchen Abhängigkeiten die Artefakte der Methode erstellt werden. Durch Zustandsautomaten wird an Komponenten beschrieben, welche alternativen Komponenten zum Austausch herangezogen werden und unter welchen Bedingungen der Austausch zur Simulationszeit stattfindet. Diese komponentenorientierte Strukturvariabilität erfordert einen neuen Übersetzungs- und Simulationsprozess, der durch die Generierung von Varianten realisiert wird. Aus den Zustandsautomaten werden Kombinationen von Komponenten abgeleitet, die zusammen mit dem unveränderlichen Teil des Modells eine Variante des Simulationsmodells ergeben. Während der Simulation sind nacheinander verschiedene Varianten aktiv. Die Simulationssteuerung überwacht die Simulation und die Austauschbedingungen der Komponenten und generiert bei Bedarf eine neue Variante und damit ein neues Gleichungssystem, das dann zur Simulation herangezogen wird. Bei einem Wechsel sind Herausforderungen wie die Übertragung und Initialisierung von Variablenwerten zu lösen. Zur Anwendung der Methode wird die prototypische Entwicklungs- und Simulationsumgebung MoVaSim vorgestellt. Sie stellt mit einem Metamodell eine Datenstruktur für die strukturvariable Ergänzung bereit. Mit Anwendung der Methode im Werkzeug werden fünf Evaluationsmodelle entwickelt und strukturvariabel simuliert. In research and development, modeling of technical systems is used to complement or replace classic prototyping. Simulation then means executing such a software model. The result of a simulation is a set of data, which, depending on the quality of the model, can draw conclusions to the technical system. Such a model consists of one differential-algebraic system of equations, which is solved numerically during simulation. Object-orientation is a concept adopted from software engineering which allows for describing highly complex models. In the domain of physical modeling, objects are known as components which consist of reusable equations. A simulation model is then composed of components with support of a development environment. Such a model has to be transformed by dissolving the hierarchy to generate the system of equations. The abstract description can result in a high level of complexity of the system of equations that is hardly solveable in an arguable time. Established simulation environments use one fixed and optimized system of equations during simulation. Therefore, capabilities to simulate fundamental changes of behavior or to adapt the granularity of equations are limited. The concept of variable-structure modeling deals with changes of the system of equations and provides possibilities to perform changes of behavior and granularity to raise efficiency. Different interpretations and prototypical realizations exist. Some of them use a special language while others use a sequence of manually generated, independent models to realize a variable-structure simulation. Until now, there has not been much effort to research on describing and performing changes of the system of equations of complex models. To fill this gap with this thesis, a description and methodology of variable-structure models is introduced on the abstract level of components. Therefore, a development process and a notation are presented, which are combined in a methodology. A prototypical development and simulation environment is shown, which supports the methodology and notation. The object-oriented language Modelica is used to describe variable-structure behavior based on the exchange of components during simulation time. The methodology extends an existing model with variable-structure behavior guided by the development process. Related artefacts are generated in a defined order. State machines for components describe, which alternative components can be used and which conditions have to be met to perform an exchange during simulation time. This component-based description of a variable-structure model requires a new translation and simulation process. With the introduction of so-called variants, an established translation process can be used while a special simulation control is presented. Derived from the state machines, combinations of components can be found, which in combination with the fixed remains of the model form a variant of the original model. During simulation different variants are successively active, each representing one system of equations. The simulation control observes the simulation as well as exchange conditions and generates new variants on demand and therefore new systems of equations, which are then used for simulation. During the switch of a variant, challenges like the transfer of values in initializations have to be performed. The methodology collects these information while the simulation control performs necessary operations. To be able to apply the proposed methodology, the prototypical development and simulation environment MoVaSim is presented. A metamodel is used as a datastructure for the variable-structure extension. By applying the methodology and with the help of the MoVaSim platform, five evaluation models are developed and simulated with variable-structure behavior.

The cogeneration of power and water in large concentrating solar power (CSP) plants with thermal storage can have significant energetic and economic benefits to supply regions with high direct irradiation and good seawater access. Due to increasing water scarcity, the Middle-East North-Africa (MENA) region has a high demand of desalinated water and a strongly increasing energy demand which cannot be completely covered using fossil fuels. In the first six chapters of the thesis, a combined approach of power generation by a solar tower plant and a thermal seawater desalination unit is examined in detail. In order to perform the analysis, the most commercialized and demonstrated technologies are derived from literature and modeled for an integrated simulation. The applied thermal desalination technology bases on a new process using an improved internal heat transfer which has been extensively tested. The obtained data have been used to derive a simulation to integrate the desalination unit as power plant condenser. The results of the energy analysis are presented by different parameter variations of boundary conditions in order to examine the most important design factors. The exergy analysis points out thermodynamic ineffciencies in certain components of the CSP plant, the heat exchangers of the desalination unit and the power plant condenser. The economic analysis focuses on capital and operational expenditures as well as the derivation of optimal cogeneration ratios based on different product prices. All simulations are carried out using real meteorological measurement data by a weather station in El Gouna, Egypt. The obtained meteorological data are compared to literature and satellite data obtained by yearly observations. In the last chapter, the simulated cogeneration system is then used to build a real demand scenario of El Gouna. The scenario is developed in order to optimize the share of renewable energy supply. This requires the integration of a photovoltaic and a wind power plant to complement the renewable power generation. The analysis shows that the integrated energy supply system covers up to 71 % of the annual energy at around 17 ¢/kWh and up to 31 % of the yearly water demand. In addition, a new process for a short-term storage of surplus power is proposed and analyzed. The surplus power is converted into heat and stored in the thermal storage system of the CSP plant which results in an extended operation time and increased capacity factor. Die Kraft-Wärme Kopplung eines großen Solarkraftwerks (CSP) mit thermischer Meerwasserentsalzung kann für die gemeinsame Erzeugung von Strom und Wasser für die Versorgung von Regionen mit hoher solarer Direktstrahlung und Meerwasserzugang erhebliche energetische und ökonomische Vorteile bieten. Vor dem Hintergrund einer Wasserknappheit und eines stark steigenden Energiebedarfs in der Middle-East North-Africa (MENA) Region muss Trinkwasser meistens aufwendig entsalzt werden, wobei die nötige Energie in Zukunft kaum noch aus fossilen Quellen gedeckt werden kann. In der vorliegenden Arbeit wird die gemeinsame Erzeugung von Strom und Wasser mittels eines Solarturmkraftwerks mit thermischen Speicher und einer neuartigen thermischen Meerwasserentsalzung detailliert analysiert. Dazu wurde in einer Literaturrecherche die effzientesten Verfahren ausgewählt und in einer Simulation integriert. Die thermische Meerwasserentsalzung nutzt einen verbesserten Prozess zur Steigerung der internen Wärmeübertragung und wurde als Kondensator des Kraftwerks in die Simulation integriert. Die Modellierung der Entsalzungsanlage wurde basierend auf den Messdaten an einer Demonstrationsanlage erarbeitet. In einer Energie- und Exergieanalyse wurden die wichtigsten Einflussgrößen auf das System mittels Parametervariation untersucht und diskutiert. Die Exergieanalyse verdeutlicht thermodynamische Ineffzienzen, die im Solarfeld, den Wärmetauschern der Meerwasserentsalzung und im Kraftwerkskondensator am größten sind. Die ökonomische Analyse beschreibt die Investitionskosten und leitet daraus ein optimales Kraft-Wärme Kopplungsverhältnis für die Strom- und Wasserproduktion in Abhängigkeit der Strompreise ab. Alle Simulationen basieren auf realen Messdaten einer meteorologischen Station in El Gouna, Ägypten, die mit Literatur- und Satellitendaten verifiziert wurden. In dem letzten Kapitel wird das modellierte System in ein reales Verbrauchszenario der Stadt El Gouna gesetzt und hinsichtlich der Deckung von Strom- und Wasserbedarf analysiert. Dazu werden zusätzliche Modelle für die Stromerzeugung aus PV und Windkraftanlagen erarbeitet. Das integrierte Energiesystem deckt bis zu 71 % des jährlichen Energiebedarfs für ca. 17 ¢/kWh und bis zu 31 % des Wasserbedarfs. Außerdem wird ein Verfahren vorgeschlagen und analysiert, mit dem Überschussstrom kurzzeitig in dem thermischen Speicher des CSP Kraftwerks gespeichert wird, um die Laufzeit des Kraftwerks zu verlängern.