@misc{10787, abstract = {{Cyber-physical production systems have emerged with the rise of Industry 4.0 in different industrial fields. Especially the food sector, where inhomogeneous input products like beer/yeast suspensions with different qualities and properties have yet slowed down automation, has potential for this evolution. This contribution presents optimization methods for a dynamical cross-flow filtration plant which is driven by an advanced control concept in combination with data driven product monitoring via inline near infrared spectroscopy (NIR) in order to improve energy savings and filtration performance. Using a hierarchical control and optimization structure, the non stationary batch process is steered towards a high production rate with low energy consumption for a variety of different input products.}}, author = {{Tebbe, Jörn and Pawlik, Thomas and Trilling-Haasler, Marc and Löbner, Jannis and Lange-Hegermann, Markus and Schneider, Jan}}, booktitle = {{2023 IEEE 21st International Conference on Industrial Informatics (INDIN)}}, editor = {{Jasperneite, Jürgen and Wisniewski, Lukasz and Fung Man, Kim}}, isbn = {{978-1-6654-9314-7 }}, issn = {{1935-4576}}, keywords = {{Spectroscopy, Production systems, Filtration, Velocity control, Optimization methods, Cyber-physical systems, Nonhomogeneous media}}, location = {{Lemgo}}, pages = {{1--7}}, publisher = {{IEEE}}, title = {{{Holistic optimization of a dynamic cross-flow filtration process towards a cyber-physical system}}}, doi = {{10.1109/INDIN51400.2023.10217913}}, year = {{2023}}, } @misc{8384, abstract = {{ynamic simulation models are widely utilized to evaluate complex technical components and systems like electric drives or machines. They can support the development process of a production machine by avoiding an inadequate layout of components or an erroneous control design. However, the effort for building them is often too high for this purpose (lot size one). An automated model generation can be utilized to overcome the gap between efforts and advantages of dynamic simulations. This contribution presents an approach for simplifying the dynamic model generation of production machines by using the so-called Asset Administration Shell defined by the initiative Platform Industrie 4.0. The Asset Administration Shell was developed to aggregate all data necessary for maintaining the product across its life cycle. This includes component data and models as well as structural information about a machine. The generation process is performed by using the common FMI standard and a two-step procedure which allows the linkage of different simulation tools. The model generation is demonstrated by an example layout of a machine's internal direct current grid.}}, author = {{Göllner, D. and Pawlik, Thomas and Schulte, Thomas}}, booktitle = {{2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)}}, isbn = {{978-1-6654-3772-1 }}, issn = {{2157-3611}}, keywords = {{Digital Twin, Asset Administration Shell, Dynamic Simulation Model, Industry 4.0, Automated Model Generation}}, location = {{Online (Singapore)}}, pages = {{808--812}}, publisher = {{IEEE}}, title = {{{Utilization of the Asset Administration Shell for the Generation of Dynamic Simulation Models}}}, doi = {{10.1109/IEEM50564.2021.9673089}}, year = {{2021}}, } @inproceedings{4026, abstract = {{The control and structural expansion of decentralized energy systems are very challenging due to the volatility of renewable energies and progressive structural changes. For balancing out seasonal fluctuations, conversions into heat or gas in combination with long-term storages are frequently discussed approaches. In context of an optimal conceptual synthesis of such systems, investigations regarding the operation and design require a large time period of at least one year. In order to solve such optimal control problems, an immense calculation time is required. This contribution presents a multistep approach which determines the optimal operation strategy in an iterative way and is capable of reducing the calculation effort. In the first step, a rough optimization incorporating a low modelling depth is performed. Especially in combination with a rough time discretization, dynamic short-term storages (e.g. electrical batteries) can become irrelevant from an optimization point of view. Therefore, the considered system can be virtually reduced by several state and control variables resulting in a significantly reduced computation time. In a second optimization, the optimal control problem is constrained using the results of the previous step. Especially the obtained values for the state of charge of the long-term storage improve significantly the quality of the second optimization. While in the first step, the dynamic programming is utilized to solve the optimal control problem in one instance, the second step uses the mixed integer linear programming to solve multiple short time periods of the optimal control problem in a sequential way. Results are presented on the basis of a simple test scenario where the electrical energy supply of a residential quarter is investigated using real photovoltaic data of one year, a modelled fuel cell system as long-term storage and an electrical battery storage as short-term storage.}}, author = {{Griese, Martin and Pawlik, Thomas and Schulte, Thomas}}, location = {{Wroclaw}}, title = {{{Optimized operation of long-term storages considering a scalable modelling depth}}}, year = {{2019}}, } @inproceedings{4024, abstract = {{For investigating combined grid systems including electrical, thermal and chemical grids, a scientific approach based on Hardware-in-the-loop simulation is carried out where models as virtual energy components are coupled with experimental facilities. In this contribution, a bidirectional fuel cell system is described in detail as a virtual energy component considering the bidirectional fuel cell, the power inverter and the local management. For modelling the bidirectional cell, the electrochemical domain is considered by a physical-based approach in a first step. Common models for unidirectional fuel cells or electrolysis cells are discussed regarding the applicability for bidirectional cells. Afterwards, the DC-DC converter as part of the overall power inverter is considered for modelling. A novel averaged model for the dual active bridge based on the method by Sanders and Verghese is presented. Finally, the overall model and local management of such systems are discussed.}}, author = {{Griese, Martin and Pawlik, Thomas and Schulte, Thomas and Maas, Jürgen}}, issn = {{2166-9546 }}, location = {{Bydgoszcz, Poland }}, pages = {{186 -- 191}}, publisher = {{IEEE}}, title = {{{Electrodynamical modelling of bidirectional fuel cell systems for HIL simulations of combined grid systems}}}, year = {{2016}}, } @inproceedings{4014, abstract = {{In this contribution, a model-based method for analysing and designing energy systems comprising the electrical, thermal and chemical domain is presented. Beside the energy generation and consumption, the bidirectional coupling between all energy domains is considered, as well. This method is an adapted variant of the so called Hardware-in-the-Loop simulation where virtual energy components are combined with geographically distributed real energy components. In order to integrate the real components with minimal instrumentation efforts, measured quantities are included as information flows, only, while the physical power flows are connected to local available grid structures. The virtual energy components are represented by real-time capable models describing their physical behaviour. In this contribution, a CHP unit is described as a virtual energy component. The modelling approach is based on a time domain approach using state variables of the multiple domains to describe the dynamic behaviour. Afterwards, the model is parameterized by datasheet specifications and measurement data of several CHP units with different power ratings. Based on these results, a method for scaling the proposed CHP model is presented. Especially for parameter studies, this method allows a simple adaption of a general parameterized CHP model. Moreover, a method for scaling such models with respect to the modelling depth is proposed and exemplarily applied to the electrical generator of the CHP model. This scaling method enables the model adaptations for different simulation purposes like detailed investigations of single structures and holistic investigations of large combined grid systems.}}, author = {{Griese, Martin and Pawlik, Thomas and Schulte, Thomas}}, booktitle = {{ International ETG Congress 2015 ; Die Energiewende - Blueprints for the new energy age}}, isbn = {{978-3-8007-4121-2}}, location = {{Bonn}}, publisher = {{VDE-Verlag}}, title = {{{Methods for scaling a physical based CHP model for HIL simulation of smart combined grid systems}}}, year = {{2015}}, } @inbook{4019, abstract = {{Im Rahmen dieses Beitrages wurde die Notwendigkeit intelligenter, gekoppelter Verbundsysteme diskutiert und ein wissenschaftlicher Ansatz zur Optimierung solcher Systeme vorgestellt. Der Ansatz basiert auf einer ganzheitlichen Betrachtung im Rahmen einer Echtzeitsimulation mit gekoppelten realen Komponenten. Zur virtuellen Koppelung wird ein Simulationsmanager eingesetzt, der eine Skalierung der realen Komponenten erlaubt. Dies ermöglicht eine einfache Adaptierung von realen und simulierten Komponenten an das jeweils betrachtete Szenario. Als eine erste simulierte Komponente wurde eine KWK-Anlage untersucht und bezüglich der elektrischen, thermischen, mechanischen und chemischen Domänen modelliert. Das Gesamtmodell berücksichtigt das Verhalten des Verbrennungsmotors, des Synchrongenerators und der Wärmeübertrager. Mit Hilfe von Messgrößen einer realen KWK-Anlage wurde im Anschluss das Gesamtmodell validiert. Die generierten Simulationsergebnisse weisen eine gute Übereinstimmung mit den erhobenen Messdaten auf. Aktuell werden weitere Energiekomponenten untersucht, um Energiesysteme ganzheitlich optimieren zu können. Dieser Beitrag ist im Rahmen des vom Land NRW geförderten Forschungsschwerpunktes „Intelligente Energiesysteme (IES)“ im Projekt „Smart Energy Village“ entstanden.}}, author = {{Schulte, Thomas and Griese, Martin and Pawlik, Thomas and Maas, Jürgen}}, booktitle = {{Detmolder Bauphysiktag 2015}}, editor = {{Schwickert, Susanne}}, isbn = {{978-3-8440-3484-4}}, pages = {{117 -- 126}}, publisher = {{Shaker Verlag}}, title = {{{Smart Energy Village – Ein Forschungsansatz für die Energieversorgung der Zukunft}}}, volume = {{2015}}, year = {{2015}}, } @inproceedings{4089, author = {{Pawlik, Thomas and Griese, Martin and Dohmann, Joachim and Maas, Jürgen and Schulte, Thomas}}, location = {{Antalya, Türkei}}, title = {{{Concept of a bidirectional Power-to-X Process System for technical and economical Investigations of Conversion and Storage Technologies}}}, year = {{2015}}, } @inproceedings{4008, abstract = {{Due to the increasing energy demand and shortage of fossil fuels, the energy systems will be transformed from mainly centralized into more decentralized systems, also incorporating more renewable energy. However, optimizing the control and structure of these systems is rather complex. A method for analyzing and planning of such systems is an adapted variant of the so called Hardware-in-the-Loop simulation. This approach comprises virtual energy components as models combined with data from experimental components. As a virtual energy component, a simulation model describing the physical behavior of CHP units is proposed in this contribution. The modeling approach is based on a time domain approach using state variables of the multiple domains to describe the dynamic behavior. For instance, the first law of thermodynamics is applied to model the thermal quantities. Furthermore, the model is scalable regarding the modeling depth and the power ratings which allows an application for different simulation scenarios. Finally, the overall model is parameterized and validated with data of a medium sized CHP plant.}}, author = {{Griese, Martin and Pawlik, Thomas and Schulte, Thomas and Maas, Jürgen}}, location = {{Istanbul}}, pages = {{189 -- 200}}, publisher = {{Academia.edu}}, title = {{{Scalable model of a CHP unit for HIL simulation of a smart combined grid system}}}, year = {{2014}}, }