TY - CHAP A1 - Pedersen, Jaap A1 - Hoppmann-Baum, Kai A1 - Zittel, Janina A1 - Koch, Thorsten T1 - Blending hydrogen into natural gas: An assessment of the capacity of the German gas grid T2 - Operations Research Proceedings 2021 N2 - In the transition towards a pure hydrogen infrastructure, repurposing the existing natural gas infrastructure is considered. In this study, the maximal technically feasible injection of hydrogen into the existing German natural gas transmission network is analysed with respect to regulatory limits regarding the gas quality. We propose a transient tracking model based on the general pooling problem including linepack. The analysis is conducted using real-world hourly gas flow data on a network of about 10,000 km length. Y1 - 2022 U6 - https://doi.org/https://doi.org/10.1007/978-3-031-08623-6_28 SP - 182 EP - 187 ER - TY - JOUR A1 - Petkovic, Milena A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Deep learning for spatio-temporal supply anddemand forecasting in natural gas transmission networks JF - Energy Science and Engineering N2 - Germany is the largest market for natural gas in the European Union, with an annual consumption of approx. 95 billion cubic meters. Germany's high-pressure gas pipeline network is roughly 40,000 km long, which enables highly fluctuating quantities of gas to be transported safely over long distances. Considering that similar amounts of gas are also transshipped through Germany to other EU states, it is clear that Germany's gas transport system is essential to the European energy supply. Since the average velocity of gas in a pipeline is only 25km/h, an adequate high-precision, high-frequency forecasting of supply and demand is crucial for efficient control and operation of such a transmission network. We propose a deep learning model based on spatio-temporal convolutional neural networks (DLST) to tackle the problem of gas flow forecasting in a complex high-pressure transmission network. Experiments show that our model effectively captures comprehensive spatio-temporal correlations through modeling gas networks and consistently outperforms state-of-the-art benchmarks on real-world data sets by at least 21%. The results demonstrate that the proposed model can deal with complex nonlinear gas network flow forecasting with high accuracy and effectiveness. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1002/ese3.932 ER - TY - GEN A1 - Pedersen, Jaap A1 - Hoppmann-Baum, Kai A1 - Zittel, Janina A1 - Koch, Thorsten T1 - Blending hydrogen into natural gas: An assessment of the capacity of the German gas grid; Technical Report N2 - In the transition towards a pure hydrogen infrastructure, utilizing the existing natural gas infrastructure is a necessity. In this study, the maximal technically feasible injection of hydrogen into the existing German natural gas transmission network is analysed with respect to regulatory limits regarding the gas quality. We propose a transient tracking model based on the general pooling problem including linepack. The analysis is conducted using real-world hourly gas flow data on a network of about 10,000 km length. T3 - ZIB-Report - 21-21 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-82838 SN - 1438-0064 ER - TY - GEN A1 - Petkovic, Milena A1 - Chen, Ying A1 - Gamrath, Inken A1 - Gotzes, Uwe A1 - Hadjidimitriou, Natalia Selini A1 - Zittel, Janina A1 - Xu, Xiaofei A1 - Koch, Thorsten T1 - A Hybrid Approach for High Precision Prediction of Gas Flows N2 - About 20% of the German energy demand is supplied by natural gas. Ad- ditionally, for about twice the amount Germany serves as a transit country. Thereby, the German network represents a central hub in the European natural gas transport network. The transport infrastructure is operated by so-called transmissions system operators or TSOs. The number one priority of the TSOs is to ensure security of supply. However, the TSOs have no knowledge of the intentions and planned actions of the shippers (traders). Open Grid Europe (OGE), one of Germany’s largest TSO, operates a high- pressure transport network of about 12.000 km length. Since flexibility and security of supply is of utmost importance to the German Energy Transition (“Energiewende”) especially with the introduction of peak-load gas power stations, being able to predict in- and out-flow of the network is of great importance. In this paper we introduce a new hybrid forecast method applied to gas flows at the boundary nodes of a transport network. The new method employs optimized feature minimization and selection. We use a combination of an FAR, LSTM DNN and mathematical programming to achieve robust high quality forecasts on real world data for different types of network nodes. Keywords: Gas Forecast, Time series, Hybrid Method, FAR, LSTM, Mathematical Optimisation T3 - ZIB-Report - 19-26 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-73525 SN - 1438-0064 ER - TY - CHAP A1 - Riedmüller, Stephanie A1 - Rivetta, Fabian A1 - Zittel, Janina T1 - Long-Term Multi-Objective Optimization for Integrated Unit Commitment and Investment Planning for District Heating Networks BT - Selected Papers of the International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), Munich, Germany, September 3-6, 2024 T2 - Operations Research Proceedings 2024 N2 - The need to decarbonize the energy system has intensified the focus on district heating networks in urban and suburban areas. Therefore, exploring transformation pathways with reasonable trade-offs between economic viability and environmental goals became necessary. We introduce a network-flow-based model class integrating unit commitment and long-term investment planning for multi-energy systems. While the integration of unit commitment and investment planning has been applied to multi-energy systems, a formal introduction and suitability for the application of long-term portfolio planning of an energy provider on an urban scale has yet to be met. Based on mixed integer linear programming, the model bridges the gap between overly detailed industrial modeling tools not designed for computational efficiency at scale and rather abstract academic models. The formulation is tested on Berlin’s district heating network. Hence, the challenge lies in a large number of variables and constraints and the coupling of time steps, for example, through investment decisions. A case study explores different solutions on the Pareto front defined by optimal trade-offs between minimizing costs and CO2 emissions through a lexicographic optimization approach. The resulting solution catalog can provide decision-makers valuable insights into feasible transformation pathways, highlighting distinctions between robust and target-dependent investments. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-92575-7_33 SP - 235 EP - 241 PB - Springer Cham ER - TY - CHAP A1 - Petkovic, Milena A1 - Zittel, Janina T1 - Resilient Forecasting of High-Dimensional Network Time Series in the Energy Domain: A Hybrid Approach T2 - Operations Research Proceedings 2023. OR 2023 N2 - Energy systems are complex networks consisting of various interconnected components. Accurate energy demand and supply forecasts are crucial for efficient system operation and decision-making. However, high-dimensional data, complex network structures, and dynamic changes and disruptions in energy networks pose significant challenges for forecasting models. To address this, we propose a hybrid approach for resilient forecasting of network time series (HRF-NTS) in the energy domain. Our approach combines mathematical optimization methods with state-of-the-art machine learning techniques to achieve accurate and robust forecasts for high-dimensional energy network time series. We incorporate an optimization framework to account for uncertainties and disruptive changes in the energy system. The effectiveness of the proposed approach is demonstrated through a case study of forecasting energy demand and supply in a complex, large-scale natural gas transmission network. The results show that the hybrid approach outperforms alternative prediction models in terms of accuracy and resilience to structural changes and disruptions, providing stable, multi-step ahead forecasts for different short to mid-term forecasting horizons. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_48 SP - 375 EP - 381 PB - Springer ER - TY - CHAP A1 - Yueksel-Erguen, Inci A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Consistent flow scenario generation based on open data for operational analysis of European gas transport networks T2 - Operations Research Proceedings 2023. OR 2023 N2 - In recent years, European gas transport has been affected by major disruptive events like political issues such as, most recently, the Russian war on Ukraine. To incorporate the impacts of such events into decision-making during the energy transition, more complex models for gas network analysis are required. However, the limited availability of consistent data presents a significant obstacle in this endeavor. We use a mathematical-modeling-based scenario generator to deal with this obstacle. The scenario generator consists of capacitated network flow models representing the gas network at different aggregation levels. In this study, we present the coarse-to-fine approach utilized in this scenario generator. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_63 SP - 493 EP - 499 PB - Springer ER - TY - JOUR A1 - Pedersen, Jaap A1 - Spreckelsen, Klaus A1 - Gotzes, Uwe A1 - Zittel, Janina A1 - Koch, Thorsten T1 - Beimischung von Wasserstoff zum Erdgas: Eine Kapazitätsstudie des deutschen Gasnetzes JF - 3R – Fachzeitschrift für Rohrleitungssystem N2 - Die europäische Gasinfrastruktur wird disruptiv in ein zukünftiges dekarbonisiertes Energiesystem verändert; ein Prozess, der angesichts der jüngsten politischen Situation beschleunigt werden muss. Mit einem wachsenden Wasserstoffmarkt wird der pipelinebasierte Transport unter Nutzung der bestehenden Erdgasinfrastruktur wirtschaftlich sinnvoll, trägt zur Erhöhung der öffentlichen Akzeptanz bei und beschleunigt den Umstellungsprozess. In diesem Fachbeitrag wird die maximal technisch machbare Einspeisung von Wasserstoff in das bestehende deutsche Erdgastransportnetz hinsichtlich regulatorischer Grenzwerte der Gasqualität analysiert. Die Analyse erfolgt auf Basis eines transienten Tracking-Modells, das auf dem allgemeinen Pooling-Problem einschließlich Linepack aufbaut. Es zeigt sich, dass das Gasnetz auch bei strengen Grenzwerten genügend Kapazität bietet, um für einen großen Teil der bis 2030 geplanten Erzeugungskapazität für grünen Wasserstoff als garantierter Abnehmer zu dienen. Y1 - 2023 IS - 06/2023 SP - 70 EP - 75 ER - TY - JOUR A1 - Pedersen, Jaap A1 - Spreckelsen, Klaus A1 - Gotzes, Uwe A1 - Zittel, Janina A1 - Koch, Thorsten T1 - Beimischung von Wasserstoff zum Erdgas: Eine Kapazitätsstudie des deutschen Gasnetzes T1 - Blending hydrogen into natural gas: An assessment of the capacity of the German gas grid JF - gwf Gas + Energie N2 - Die europaische Gasinfrastruktur wird disruptiv in ein zukunftiges dekarbonisiertes Energiesystem verändert; ein Prozess, der angesichts der jüngsten politischen Situation beschleunigt werden muss. Mit einem wachsenden Wasserstoffmarkt wird der pipelinebasierte Transport unter Nutzung der bestehenden Erdgasinfrastruktur wirtschaftlich sinnvoll, trägt zur Erhöhung der öffentlichen Akzeptanz bei und beschleunigt den Umstellungsprozess. In diesem Beitrag wird die maximal technisch machbare Einspeisung von Wasserstoff in das bestehende deutsche Erdgastransportnetz hinsichtlich regulatorischer Grenzwerte der Gasqualität analysiert. Die Analyse erfolgt auf Basis eines transienten Tracking-Modells, das auf dem allgemeinen Pooling-Problem einschließlich Linepack aufbaut. Es zeigt sich, dass das Gasnetz auch bei strengen Grenzwerten gen ̈ugend Kapazität bietet, um für einen großen Teil der bis 2030 geplanten Erzeugungskapazität für grünen Wasserstoff als garantierter Abnehmer zu dienen. N2 - The European gas infrastructure is being disruptively transformed into a future decarbonised energy system; a process that needs to be accelerated given the recent political situation. With a growing hydrogen market, pipeline-based transport using the existing natural gas infrastructure becomes economically viable, helps to increase public acceptance and accelerates the transition process. In this paper, the maximum technically feasible feed-in of hydrogen into the existing German natural gas transport network is analysed with regard to regulatory limits of gas quality. Analysis is based on a transient tracking model that builds on the general pooling problem including linepack. It is shown that even with strict limits, the gas grid offers sufficient capacity to serve as a guaranteed customer for a large part of the green hydrogen generation capacity planned until 2030. Y1 - 2023 PB - Vulkan Verlag ET - 06/2023 ER - TY - CHAP A1 - Petkovic, Milena A1 - Zakiyeva, Nazgul A1 - Zittel, Janina T1 - Statistical Analysis and Modeling for Detecting Regime Changes in Gas Nomination Time Series T2 - Operations Research Proceedings 2021. OR 2021 N2 - As a result of the legislation for gas markets introduced by the European Union in 2005, separate independent companies have to conduct the transport and trading of natural gas. The current gas market of Germany, which has a market value of more than 54 billion USD, consists of Transmission System Operators (TSO), network users, and traders. Traders can nominate a certain amount of gas anytime and anywhere in the network. Such unrestricted access for the traders, on the other hand, increase the uncertainty in the gas supply management. Some customers’ behaviors may cause abrupt structural changes in gas flow time series. In particular, it is a challenging task for the TSO operators to predict gas nominations 6 to 10 h-ahead. In our study, we aim to investigate the regime changes in time series of nominations to predict the 6 to 10 h-ahead of gas nominations. Y1 - 2022 U6 - https://doi.org/10.1007/978-3-031-08623-6_29 SP - 188 EP - 193 PB - Springer, Cham ER - TY - CHAP A1 - Lindner, Niels A1 - Bartoszuk, Karolina A1 - Debgupta, Srinwanti A1 - Gering, Marie-Claire A1 - Muschner, Christoph A1 - Zittel, Janina T1 - Warm-starting modeling to generate alternatives for energy transition paths in the Berlin-Brandenburg area T2 - Operations Research Proceedings 2024. OR 2024 N2 - Energy system optimization models are key to investigate energy transition paths towards a decarbonized future. Since this approach comes with intrinsic uncertainties, it is insufficient to compute a single optimal solution assuming perfect foresight to provide a profound basis for decision makers. The paradigm of modeling to generate alternatives enables to explore the near-optimal solution space to a certain extent. However, large-scale energy models require a non-negligible computation time to be solved. We propose to use warm start methods to accelerate the process of finding close-to-optimal alternatives. In an extensive case study for the energy transition of the Berlin-Brandenburg area, we make use of the sector-coupled linear programming oemof-B3 model to analyze a scenario for the year 2050 with a resolution of one hour and 100% reduction of greenhouse gas emissions. We demonstrate that we can actually achieve a significant computational speedup. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-92575-7_35 SP - 248 EP - 253 ER - TY - CHAP A1 - Stompor, Tomasz A1 - Zittel, Janina A1 - Koch, Thorsten A1 - Rusch, Beate T1 - Fully Algorithmic Librarian: Large-Scale Citation Experiments T2 - 20th International Society of Scientometrics and Informetrics Conference 2025, June 23-27, 2025 | Yerevan, Armenia N2 - The Fully Algorithmic Librarian (FAN) project explores application scenarios for algorithmic-intelligence(AI)-supported methods in academic libraries as central institutions for research support. To this end, the study builds on two algorithmic approaches for analyzing large-scale citation networks. A comparison of Web of Science (WoS) and OpenAlex structures using the PageRank algorithm reveals key differences. Additionally, a multi-label clustering technique designed for large-scale citation networks accounts for disciplinary variations in publication practices. Y1 - 2025 U6 - https://doi.org/10.51408/issi2025_204 ER -