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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Shreyas Parbat Imam Iqbal Isabell Viedt Leon Urbas Chair of Process Control Systems & Process Systems Engineering Group Technische Universität Dresden Dresden Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Waste and recycling material sorting is crucial for reducing environmental impact and promoting resource recovery. However, its complexity poses significant challenges, necessitating the development of effective sorting processes. Manual operation of these plants can be less efficient than automated systems. The first step toward automation is utilizing a Digital Twin, which combines fundamental principles and data-driven insights into the waste sorting process. To achieve this, the equipment involved in waste sorting plants can be analyzed in detail, focusing on operational settings and their impact on overall efficiency. Initially, a steady-state model of the plant is developed, followed by the implementation of advanced strategies like model predictive control. The model can be rigorously tested and refined using a case study on German post-consumer waste. The architecture of the Digital Twin, comprising various building blocks such as the modeling and simulation block, is being developed to transition away from manual operations. This Digital Twin aims to enhance sorting efficiency through offline and online optimization of operational set points, leading to a more sustainable and resource-efficient future. Through simulations and real-time data integration, a Digital Twin for the waste and recycling material process can aid with process design, fine-tuning, and plant automation.

关键词： process design Predictive models Real-time systems Digital twins Recycling Steady-state Optimization Manufacturing automation Sorting Predictive control

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Demonstrating Containerization of Model Predictive control for Modular Plants

Demonstrating Containerization of Model Predictive Control f...

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Industrial Cyber-Physical systems (ICPS)

作者： Lucas Vogt Zohra Charania Jonathan Mädler Julius Lorenz Helaleh Badrnoebashar Amy Koch Leon Urbas Process-to-Order Lab TU Dresden Dresden Germany Chair of Process Control Systems TU Dresden Dresden Germany Process Systems Engineering Group TU Dresden Dresden Germany

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

Model predictive control has the potential to increase yields in the process industry, but its deployment is limited by high computational cost. In multi-purpose, modular plant concepts, it is particularly difficult to predict the whole variety of products for which a specific module will be used throughout its lifespan. During module manufacturing, this results in the challenge of allocating the correct computing, memory, and communication capacities to a module so that a model-predictive control application with currently unknown hardware requirements can be used later. The difficulty of this task often prevents the desirable deployment of model predictive control in production environments. The aim of this publication is therefore to demonstrate a simplified deployment and reconfiguration of model predictive control applications for modular plants through containerization. After an overview of the current state of the art, we present the underlying automation architecture based on modular plant concepts combined with a cloud-like automation approach enabled by containerization of the control applications. The feasibility of the chosen approach is demonstrated by implementing a proof-of-concept demonstrator. Subsequently, lessons learned from the demonstrator are discussed and future improvement potentials are identified, which will be the subject of future research.

关键词： Industries Automation Memory management Production Software Hardware Manufacturing

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Operation Strategies for Modular Large-Scale Alkaline Electrolysis systems

Operation Strategies for Modular Large-Scale Alkaline Electr...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Hannes Lange Christioph Schirmer Michael Mock Isabell Viedt Anselm Klose Leon Urbas Process Systems Engineering Group TUD Dresden University of Technology Dresden Germany Chair of Process Control Systems TUD Dresden University of Technology Dresden Germany

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

In this paper we compare different operation strategies for alkaline electrolyzis (AEL) systems using numeric simulation. We derived general models for mass and energy balances from literature and composed them into a model for an AEL system. Here we considered a numbered-up plant topology, containing multiple AEL stacks with single electrolyte distribution and gas separation systems. The gas impurities and achievable minimal load distribution were compared for the different operating strategies. The results were discussed and further conclusions for the operation of a homogeneous numbered-up AEL system were derived.

关键词： Impurities Electrolytes Numerical models Topology Electrochemical processes Informatics Load modeling

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A Prototype for Navigation in Signed Directed Graphs of Chemical processes

A Prototype for Navigation in Signed Directed Graphs of Chem...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Nazanin Hamedi Julia Richter Bernhard Schrank Eric Lischinski Jiaxin Chen Xiaoyu Sun Anselm Klose Leon Urbas DFG RTG Conducive Design of Cyber Physical Systems TU Dresden Dresden Germany Chair of Process Control Systems TU Dresden Dresden Germany Chair of Process Control Systems Process-to-Order Lab TU Dresden Dresden Germany Process Control Systems & Process Systems Engineering TU Dresden Dresden Germany

Signed Directed Graphs (SDGs) are among the very beneficial, and well-known tools for fault diagnosis in chemical process plants. Based on the size of the process plant, their corresponding SDGs can be very large in size; and therefore, significantly difficult to navigate. Besides that, the recent advancement in semantic description of process structures and intelligent process and Instrumentation Diagrams (P&IDs), has led to the development of several computer tools for navigating in a process plant structure and examining the connectivity of different process equipment to each other. In this study a prototype for an intelligent P&ID, in which the SDG is considered to help the user understand the influence of process parameters on each other is developed. Requirements were derived and implemented as a click prototype, using Axure RP. The evaluation results indicate that despite the high understandability of the prototype, the cognitive efforts for linking the information derived from the SDG with the plant’s P&ID scheme are still too high for achieving a good overall usability.

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Application of an electrolysis system model for techno-economic optimization of hydrogen production in industry-based case studies

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International Journal of Hydrogen Energy 2025年 138卷 1144-1162页

作者： Köstlbacher, Jürgen Breuning, Larissa Nigbur, Florian Wienert, Patrick Khatiwada, Dilip Technical University of Munich School of Engineering and Design Department of Energy and Process Engineering Chair of Renewable and Sustainable Energy Systems Lichtenbergstraße 4a Garching bei Muenchen85748 Germany KTH Royal Institute of Technology Department of Energy Technology Division of Energy System Brinellvägen 68 Stockholm100 44 Sweden Accenture Germany Campus Kronberg 1 Kronberg61476 Germany

Even with favorable policy frameworks, green hydrogen has not been cost-competitive in Europe. Optimizing hydrogen production can reduce the Levelized Costs of Hydrogen (LCOH). In this research, an electrolysis system model is developed to optimize hydrogen production in two industrial settings. The model incorporates technical aspects such as part-load behavior, stack degradation, and energy inputs (i.e., electricity price and volume projections). Mid-scale hydrogen production for heavy-duty transport refuelling in Germany has the lowest LCOH at 8 €/kg (with a 16 MWel electrolysis system), whereas large-scale hydrogen production for the refinery industry in Portugal achieves 4 €/kg (with a 128 MWel system). The study reveals that the optimal system configuration depends on energy prices, technology costs, efficiency, load flexibility, and storage options. This study could be helpful in operationalizing hydrogen production systems (e.g., stack operation and replacement strategies) depending on energy supply and hydrogen demand over the lifetime. © 2025 The Authors

关键词： Linear programming

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Standards for Information Models Considering Knowledge Distribution in Modular Plants

Standards for Information Models Considering Knowledge Distr...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Amy Koch Nazanin Hamedi Lukas Furtner Tobias Kock Anselm Klose Jonathan Mädler Process Systems Engineering Group TU Dresden Dresden Germany Research Training Group 2323 TU Dresden Dresden Germany Chair of Process Control Systems Process-to-Order Lab TU Dresden Dresden Germany

For various applications, information models described in standards are available to enable a digital data exchange. For modular process plants, where different domains are interacting in different phases of the plant lifecycle, single, existing standards are not *** this work, we analyze the most relevant standards for process engineering, namely OntoCAPE, DEXPI, and IEC 61512, in regards to their application to support the lifecycle of modular process plants, which are described in the VDI 2776 and VDI/VDE/NAMUR 2658 standards. By challenging the standards with competency questions derived from a specific use case, we discuss which information models are most suitable for all individual domains in each lifecycle phase. The result is the specification of parts of these standards which are needed to create a fully digital support for modular process plants on the example of the introduced use case.

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process control Principles for Scalable Electrolysis systems

Process Control Principles for Scalable Electrolysis Systems

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Julius Lorenz Anselm Klose Hannes Lange Tobias Kock Leon Urbas Chair of Process Control Systems TUD Dresden University of Technology Dresden Germany Process to Order Lab TUD Dresden University of Technology Dresden Germany Process Systems Engineering Group TUD Dresden University of Technology Dresden Germany

The scale up of hydrogen production to large scale production systems demands a structured approach to control these systems. With suitable control principles, optimization for operation can be achieved whilst maintaining flexibility. In this paper, existing control strategies are analyzed and compared for large scale electrolysis systems. It is argued, how modularization can enable the optimal distribution of set-points and enables the systems for capacity extension. An initial implementation in MATLAB is presented, showing the feasibility of the proposed power distribution concept.

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Flexible process control for Scalable Electrolysis systems

Flexible Process Control for Scalable Electrolysis Systems

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Electrical, Computer and Energy Technologies (ICECET), International Conference on

Large-scale water electrolysis systems are built from a multitude of stack units. These stack units have to be controlled during operation. The question arises how process control of the system can be designed in that way, that scalable, extendable but also optimal operation of the stack units becomes possible. To achieve this goal, existing process control strategies from literature are analyzed. The requirements resulting from the inherent numbering up of stack units are described and an approach for an adaptable optimized process control strategy considering the system properties is proposed. The proposed process control strategy is implemented in a modeled electrolysis system and evaluated regarding the stated criteria. The results could show, that the inherent modularization of electrolysis systems can be used in advantage for a scalable operation.

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A Numerical Study on the Parallelization of Dual Decomposition-based Distributed Mixed-Integer Programming

A Numerical Study on the Parallelization of Dual Decompositi...

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European control Conference (ECC)

作者： Mario Klostermeier Vassilios Yfantis Achim Wagner Martin Ruskowski Department of Mechanical and Process Engineering Chair of Machine Tools and Control Systems University of Kaiserslautern-Landau Kaiserslautern Germany German Research Center for Artificial Intelligence (DFKI) Kaiserslautern Germany

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

The shift from centralized to decentralized systems is increasing the complexity of many problems in control and optimization. However, it also presents the opportunity to exploit parallelized computational schemes. This paper shows how the solution process of mixed-integer problems, which often arise in areas like production scheduling or logistics, can be supported by employing parallel computations. To this end, dual variables are introduced that enable the decomposition of these complex problems into subproblems that can then be solved in parallel. The presented dual decomposition-based approach provides a lower bound for the optimal solution of the original problem, which can support the overall solution process. The focus of this paper is on the parallelizability of the computation of this lower bound. The bounds from three different dual decomposition- based distributed optimization algorithms are compared to the lower bounds provided by several commercial solvers within their branch-&-cut framework.

关键词： processor scheduling Europe Production Programming Complexity theory Optimization Logistics

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Model Predictive control Based Reference Generation for Optimal Proportional Integral Derivative control

Model Predictive Control Based Reference Generation for Opti...

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Mediterranean Conference on control and Automation (MED)

作者： Fatos Gashi Khalil Abuibaid Martin Ruskowski Achim Wagner German Research Center for Artificial Intelligence (DFKI) Kaiserslautern Germany Department of Mechanical and Process Engineering Chair of Machine Tools and Control Systems RPTU Kaiserslautern-Landau Kaiserslautern Germany

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

We introduce an alternative approach towards optimal proportional integral derivative (PID) control, consisting of model predictive control (MPC) based reference generation. To this end, we have integrated the reference as part of optimization variables of the resulting problem, where a deliberate sequence of errors is induced to obtain an optimal PID control action. In addition, the desired behavior of the PID controller is achieved without the need for internal modification of the PID gains. To better highlight the ability of coping with poor PID tuning, several test cases consisting of progressively degraded PID gains are presented. Validation of the proposed strategy is displayed by comprehensive simulations using two different plants.

关键词： PI control Automation PD control Tuning Optimization Predictive control

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