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Open Source Modelling and Simulation of Energy Systems (OSMSES)

作者： Jianlei Liu Malte Chlosta Nicolas Schaber Jannik Sidler Richard Lutz Thorsten Schlachter Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany

Scientists and engineers involved in the design of complex system solutions use computational Workflows and co-simulations to explore, model, and evaluate the behavior of these system solutions. With the help of integration tools, scientists and engineers can avoid the implementation of additional interfaces when coupling different executables and running them as an overall system solution, which hinders their original research or engineering goals. Therefore, a novel framework named PROcess Orchestration Framework (PROOF) for streamlining the creation and automation of computational workflows and co-simulations is introduced in this article. It uses state-of-the-art technologies for automation (e.g., container virtualization) and coordination (e.g., distributed message-oriented middleware). It supports task parallelism and recoverability capabilities by utilizing container orchestration on a distributed computing cluster. PROOF uses a descriptive approach to abstractly create workflows with the help of a scalable and extendable user interface.

关键词： Couplings automation Message-oriented middleware Computational modeling Containers User interfaces Parallel processing

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Design-and Simulation of a Body-Worn Optical Xylene Measuring Device for Use in Pathology

Design-and Simulation of a Body-Worn Optical Xylene Measurin...

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Design, Test, Integration and Packaging of MEMS/MOEMS

作者： Ingo Sieber Alen Deleut Lisa Petani Christian Pylatiuk Institute for Automation and Applied Informatics (IAI) Karlsruhe Institiute of Technology (KIT) Karlsruhe Germany

ISBN: (数字)9798350378269

ISBN: (纸本)9798350378276

In pathology, xylene is used in various process steps to prepare tissue samples for further examination and is essential despite potential health risks. To protect employees, it is desirable to monitor exposures to individuals using a wearable detector. This article presents the design and simulation of a xylene measuring device based on a multi pass cell, which is the size of a smartphone and thus allows the measuring unit to be worn comfortably on the body. The geometrical and metrological requirements result in a beam path of approximately 2000 mm, folded to such an extent that it undercuts 28 reflections on its path.

关键词： Pathology Optical design Optical variables measurement Packaging Optical detectors Size measurement Reflection

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Advancing Distributed Ac Optimal Power Flow for Integrated Transmission-Distribution Systems

SSRN

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SSRN 2024年

作者： Dai, Xinliang Zhai, Junyi Jiang, Yuning Guo, Yi Jones, Colin N. Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany China Switzerland Switzerland

This paper introduces a distributed operational solution for integrated transmission-distribution (ITD) system management. A fundamental challenge in designing distributed approaches for AC optimal power flow (OPF) problems in ITD systems is the nonconvexity and nonlinearity of the optimization problems for both transmission and distribution systems. To tackle the challenges, our research introduces an enhanced version of the Augmented Lagrangian based Alternating Direction Inexact Newton method (aladin), which incorporates a second-order correction strategy and convexification. The former improves the algorithm’s ability to follow curved trajectories effectively with minimal additional computational demand, while the latter simplifies the decoupled subproblems without introducing the combinatory complexity typically associated with additional inequality constraints. The theoretical studies demonstrate that the proposed distributed algorithm operates the ITD systems with a local quadratic convergence guarantee. Extensive simulations on various ITD configurations highlight the superior performance of our distributed approach in terms of convergence speed, computational efficiency, scalability, and adaptability. © 2024, The Authors. All rights reserved.

关键词： Constrained optimization

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Challenges in Developing Digital Twins for Labor-intensive Manufacturing Systems: A Step towards Human-centricity 15

Challenges in Developing Digital Twins for Labor-intensive M...

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15th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2024 / The 7th International Conference on Emerging Data and Industry 4.0, EDI40 2024

作者： Götz, Manuel Lazarova-Molnar, Sanja Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Kaiserstr 89 Karlsruhe76133 Germany Mcersk Mc-Kinney Moller Institute University of Southern Denmark Campusvej 55 Odense5230 Denmark

Many existing manufacturing systems still rely heavily on human workers as the backbone of their production processes. Such systems are commonly termed labor-intensive. Developing Digital Twins for labor-intensive manufacturing lines is a complex and challenging task as human involvement adds another level of uncertainty. While Digital Twins offer numerous benefits, such as improved efficiency, reduced downtime, and enhanced decision-making, they also come with unique challenges when they need to be developed for labor-intensive manufacturing systems. In this paper, we discuss the main challenges and their implications that arise from existing research. Considering these challenges, we propose a framework for developing data-driven Digital Twins of labor-intensive manufacturing systems as an initial step towards addressing these challenges. We illustrate the challenges associated with Digital Twins of labor-intensive manufacturing systems through a practical case study derived from our collaboration with two companies. In the case study, we make necessary preparations for developing Digital Twins for decision support in job scheduling in a hybrid machine-worker environment while considering the well-being of workers. © 2024 Elsevier B.V.. All rights reserved.

关键词： Decision making

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Towards Fusing Data and Expert Knowledge for Better-Informed Digital Twins: An Initial Framework 15

Towards Fusing Data and Expert Knowledge for Better-Informed...

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15th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2024 / The 7th International Conference on Emerging Data and Industry 4.0, EDI40 2024

作者： Jungmann, Michelle Lazarova-Molnar, Sanja Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Kaiserstr 89 Karlsruhe76133 Germany Mcersk Mc-Kinney Moller Institute University of Southern Denmark Campusvej 55 Odense5230 Denmark

Data-driven Digital Twin approaches have gained popularity in research literature, particularly in relation to Industry 4.0 achievements. Data-driven Digital Twins process widely available real-time data in an automated manner to extract models from various systems of interest. However, these model extraction approaches commonly lack systematic integration of expert knowledge from human experts, such as engineers. Combining valuable expert knowledge with data-driven model extraction approaches is a highly complex task that can significantly contribute to more accurate models within shorter time periods. In this paper, we provide a comprehensive overview of the research done on fusion of data and expert knowledge for Digital Twins to identify and describe the current gap. Resulting from our findings, we propose an initial framework for integrating expert knowledge and data for Digital Twin model extraction. Subsequently, we provide an overview of the main challenges and opportunities in fusing data and expert knowledge in the context of Digital Twins. © 2024 Elsevier B.V.. All rights reserved.

关键词： Industry 4.0

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Towards a Real-World Dispatchable Feeder

Towards a Real-World Dispatchable Feeder

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IEEE Electronic Power Grid (eGrid)

作者： Sebastian Beichter Maximilian Beichter Dorina Werling Johannes Galenzowski Victor Weise Christoph Hildenbrand Friedrich Wiegel Ralf Mikut Simon Waczowicz Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany

With the integration of renewable energy sources, electric vehicles, and batteries at the low-voltage distribution grid level, residential buildings are increasingly evolving from consumers to prosumers. As the prosumers burden the distribution grid with their uncertain interactions, the need for solutions to counteract this uncertainty becomes more important. One such solution is schedule-based control strategies, such as the dispatchable feeder. Thereby, the dispatchable feeder uses intelligent managed flexible components such as battery energy storage system (BESS) and controllable loads to follow a committed schedule. While the concept of the dispatchable feeder is widely discussed in the literature, the practical challenges associated with its real-world implementation remain under-explored. Therefore, this paper identifies challenges associated with the real-world implementation of the dispatchable feeder in residential buildings. Further, it discusses important future research questions regarding the concept and its valuable integration into the real world. It also proposes an experimental research infrastructure for systematically investigating the raised questions using the real-world laboratory of the Energy Lab 2.0.

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Transformer Training Strategies for Forecasting Multiple Load Time Series

arXiv

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arXiv 2023年

作者： Hertel, Matthias Beichter, Maximilian Heidrich, Benedikt Neumann, Oliver Schäfer, Benjamin Mikut, Ralf Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany

In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the number of monitored clients will increase with the ongoing smart meter rollout, the amount of data per client will always be limited. We evaluate whether a Transformer load forecasting model benefits from a transfer learning strategy, where a global univariate model is trained on the load time series from multiple clients. In experiments with two datasets containing load time series from several hundred clients, we find that the global training strategy is superior to the multivariate and local training strategies used in related work. On average, the global training strategy results in 21.8% and 12.8% lower forecasting errors than the two other strategies, measured across forecasting horizons from one day to one month into the future. A comparison to linear models, multi-layer perceptrons and LSTMs shows that Transformers are effective for load forecasting when they are trained with the global training strategy. © 2023, CC BY.

关键词： Forecasting

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Probabilistic Forecasting of Day-Ahead Electricity Prices and their Volatility with LSTMs

Probabilistic Forecasting of Day-Ahead Electricity Prices an...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Trebbien, Julius Pütz, Sebastian Schäfer, Benjamin Nygård, Heidi S. Gorjão, Leonardo Rydin Witthaut, Dirk Forschungszentrum Jülich Jülich Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany Faculty of Science and Technology Norwegian University of Life Sciences Ås Norway

ISBN: (纸本)9798350396782

Accurate forecasts of electricity prices are crucial for the management of electric power systems and the development of smart applications. European electricity prices have risen substantially and became highly volatile after the Russian invasion of Ukraine, challenging established forecasting methods. Here, we present a Long Short-Term Memory (LSTM) model for the German-Luxembourg day-ahead electricity prices addressing these challenges. The recurrent structure of the LSTM allows the model to adapt to trends, while the joint prediction of both mean and standard deviation enables a probabilistic prediction. Using a physics-inspired approach – superstatistics – to derive an explanation for the statistics of prices, we show that the LSTM model faithfully reproduces both prices and their volatility. © 2023 IEEE.

关键词： day-ahead electricity prices Electricity prices German-Luxembourg electricity prices heavy tailed distributions LSTM probabilistic forecasting superstatistics volatility

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Application of Model-Free Control to Reduce the Total Harmonic Distortion of Inverters

Application of Model-Free Control to Reduce the Total Harmon...

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IEEE Electronic Power Grid (eGrid)

作者： Jan Wachter Lutz Gröll Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

With the fast rising number of power electronic devices in the electric grid, the harmonic emissions of those devices can lead to significant power quality issues. This is reflected in the recent addition of harmonic stability as one of the grid stability types. The reduction of harmonic emissions is an important task in the development of resilient carbon neutral grids. This paper describes the application of the model-free control concept for grid-tied inverters as an easily implementable extension for dq0-frame based current control loops, which are often used in cascaded control schemes. The approach incorporates the information contained in the output current derivative. To balance phase-error and measurement noise suppression, the derivative is obtained using an algebraic numerical differentiator. The reduction of the total harmonic distortion (THD) is demonstrated for two use-cases in simulation, in order to show the transferability of the results. Further, measurement data from a hardware implementation of the concept is studied to verify the behavior under real-world conditions. For this, the influence of the tuning parameters is discussed along with limitations of the approach.

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From News to Summaries: Building a Hungarian Corpus for Extractive and Abstractive Summarization 30

From News to Summaries: Building a Hungarian Corpus for Extr...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Barta, Botond Lakatos, Dorina Nagy, Attila Nyist, Milán Konor Ács, Judit HUN-REN Institute for Computer Science and Control Hungary Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary

ISBN: (纸本)9782493814104

Training summarization models requires substantial amounts of training data. However for less resourceful languages like Hungarian, openly available models and datasets are notably scarce. To address this gap our paper introduces HunSum-2 an open-source Hungarian corpus suitable for training abstractive and extractive summarization models. The dataset is assembled from segments of the Common Crawl corpus undergoing thorough cleaning, preprocessing and deduplication. In addition to abstractive summarization we generate sentence-level labels for extractive summarization using sentence similarity. We train baseline models for both extractive and abstractive summarization using the collected dataset. To demonstrate the effectiveness of the trained models, we perform both quantitative and qualitative evaluation. Our dataset, models and code are publicly available, encouraging replication, further research, and real-world applications across various domains. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： abstractive summarization extractive summarization Hungarian

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