@inproceedings{YuekselErguenKochZittel, author = {Yueksel-Erguen, Inci and Koch, Thorsten and Zittel, Janina}, title = {Consistent flow scenario generation based on open data for operational analysis of European gas transport networks}, series = {Operations Research Proceedings 2023}, booktitle = {Operations Research Proceedings 2023}, abstract = {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.}, language = {en} } @article{PetkovicKochZittel, author = {Petkovic, Milena and Koch, Thorsten and Zittel, Janina}, title = {Deep learning for spatio-temporal supply anddemand forecasting in natural gas transmission networks}, series = {Energy Science and Engineering}, journal = {Energy Science and Engineering}, doi = {https://doi.org/10.1002/ese3.932}, abstract = {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.}, language = {en} } @article{PetkovicChenGamrathetal., author = {Petkovic, Milena and Chen, Ying and Gamrath, Inken and Gotzes, Uwe and Hadjidimitrou, Natalia Selini and Zittel, Janina and Xu, Xiaofei and Koch, Thorsten}, title = {A hybrid approach for high precision prediction of gas flows}, series = {Energy Systems}, volume = {13}, journal = {Energy Systems}, doi = {10.1007/s12667-021-00466-4}, pages = {383 -- 408}, abstract = {About 23\% of the German energy demand is supplied by natural gas. Additionally, for about the same 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 transmissions system operators (TSOs). The number one priority of the TSOs is to ensure the security of supply. However, the TSOs have only very limited knowledge about 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. With the introduction of peak-load gas power stations, it is of great importance to predict in- and out-flow of the network to ensure the necessary flexibility and security of supply for the German Energy Transition ("Energiewende"). In this paper, we introduce a novel hybrid forecast method applied to gas flows at the boundary nodes of a transport network. This method employs an optimized feature selection and minimization. We use a combination of a FAR, LSTM and mathematical programming to achieve robust high-quality forecasts on real-world data for different types of network nodes.}, language = {en} } @article{PedersenSpreckelsenGotzesetal., author = {Pedersen, Jaap and Spreckelsen, Klaus and Gotzes, Uwe and Zittel, Janina and Koch, Thorsten}, title = {Beimischung von Wasserstoff zum Erdgas: Eine Kapazit{\"a}tsstudie des deutschen Gasnetzes}, series = {gwf Gas + Energie}, journal = {gwf Gas + Energie}, edition = {06/2023}, publisher = {Vulkan Verlag}, abstract = {Die europaische Gasinfrastruktur wird disruptiv in ein zukunftiges dekarbonisiertes Energiesystem ver{\"a}ndert; ein Prozess, der angesichts der j{\"u}ngsten politischen Situation beschleunigt werden muss. Mit einem wachsenden Wasserstoffmarkt wird der pipelinebasierte Transport unter Nutzung der bestehenden Erdgasinfrastruktur wirtschaftlich sinnvoll, tr{\"a}gt zur Erh{\"o}hung der {\"o}ffentlichen 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 Gasqualit{\"a}t 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 Kapazit{\"a}t bietet, um f{\"u}r einen großen Teil der bis 2030 geplanten Erzeugungskapazit{\"a}t f{\"u}r gr{\"u}nen Wasserstoff als garantierter Abnehmer zu dienen.}, language = {de} } @article{PedersenSpreckelsenGotzesetal., author = {Pedersen, Jaap and Spreckelsen, Klaus and Gotzes, Uwe and Zittel, Janina and Koch, Thorsten}, title = {Beimischung von Wasserstoff zum Erdgas: Eine Kapazit{\"a}tsstudie des deutschen Gasnetzes}, series = {3R - Fachzeitschrift f{\"u}r Rohrleitungssystem}, journal = {3R - Fachzeitschrift f{\"u}r Rohrleitungssystem}, number = {06/2023}, pages = {70 -- 75}, abstract = {Die europ{\"a}ische Gasinfrastruktur wird disruptiv in ein zuk{\"u}nftiges dekarbonisiertes Energiesystem ver{\"a}ndert; ein Prozess, der angesichts der j{\"u}ngsten politischen Situation beschleunigt werden muss. Mit einem wachsenden Wasserstoffmarkt wird der pipelinebasierte Transport unter Nutzung der bestehenden Erdgasinfrastruktur wirtschaftlich sinnvoll, tr{\"a}gt zur Erh{\"o}hung der {\"o}ffentlichen 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 Gasqualit{\"a}t 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{\"u}gend Kapazit{\"a}t bietet, um f{\"u}r einen großen Teil der bis 2030 geplanten Erzeugungskapazit{\"a}t f{\"u}r gr{\"u}nen Wasserstoff als garantierter Abnehmer zu dienen.}, language = {de} } @article{PedersenLeKochetal., author = {Pedersen, Jaap and Le, Thi Thai and Koch, Thorsten and Zittel, Janina}, title = {Optimal discrete pipe sizing for tree-shaped CO2 networks}, series = {OR Spectrum}, journal = {OR Spectrum}, doi = {10.1007/s00291-024-00773-z}, abstract = {For industries like the cement industry, switching to a carbon-neutral production process is impossible. They must rely on carbon capture, utilization and storage (CCUS) technologies to reduce their production processes' inevitable carbon dioxide (CO2) emissions. For transporting continuously large amounts of CO2, utilizing a pipeline network is the most effective solution; however, building such a network is expensive. Therefore minimizing the cost of the pipelines to be built is extremely important to make the operation financially feasible. In this context, we investigate the problem of finding optimal pipeline diameters from a discrete set of diameters for a tree-shaped network transporting captured CO2 from multiple sources to a single sink. The general problem of optimizing arc capacities in potential-based fluid networks is already a challenging mixed-integer nonlinear optimization problem. The problem becomes even more complex when adding the highly sensitive nonlinear behavior of CO2 regarding temperature and pressure changes. We propose an iterative algorithm splitting the problem into two parts: a) the pipe-sizing problem under a fixed supply scenario and temperature distribution and b) the thermophysical modeling, including mixing effects, the Joule-Thomson effect, and heat exchange with the surrounding environment. We demonstrate the effectiveness of our approach by applying our algorithm to a real-world network planning problem for a CO2 network in Western Germany. Further, we show the robustness of the algorithm by solving a large artificially created set of network instances.}, language = {en} } @inproceedings{PedersenHoppmannBaumZitteletal., author = {Pedersen, Jaap and Hoppmann-Baum, Kai and Zittel, Janina and Koch, Thorsten}, title = {Blending hydrogen into natural gas: An assessment of the capacity of the German gas grid}, series = {Operations Research Proceedings 2021}, booktitle = {Operations Research Proceedings 2021}, doi = {https://doi.org/10.1007/978-3-031-08623-6_28}, pages = {182 -- 187}, abstract = {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.}, language = {en} } @article{HoppmannBaumHenningsZitteletal., author = {Hoppmann-Baum, Kai and Hennings, Felix and Zittel, Janina and Gotzes, Uwe and Spreckelsen, Eva-Maria and Spreckelsen, Klaus and Koch, Thorsten}, title = {An Optimization Approach for the Transient Control of Hydrogen Transport Networks}, series = {Mathematical Methods of Operations Research}, journal = {Mathematical Methods of Operations Research}, number = {Special Issue on Energy Networks}, language = {en} } @misc{CharoussetBrignolvanAckooijOudjaneetal., author = {Charousset-Brignol, Sandrine and van Ackooij, Wim and Oudjane, Nadia and Daniel, Dominique and Noceir, Slimane and Haus, Utz-Uwe and Lazzaro, Alfio and Frangioni, Antonio and Lobato, Rafael and Ghezelsoflu, Ali and Iardella, Niccol{\`o} and Galli, Laura and Gorgone, Enrico and dell'Amico, Mauro and Giannelos, Spyros and Moreira, Alex and Strbac, Goran and Borozan, Stefan and Falugi, Paula and Pudjianto, Danny and Wyrwoll, Lothar and Schmitt, Carlo and Franken, Marco and Beulertz, Daniel and Schwaeppe, Henrik and Most, Dieter and Y{\"u}ksel-Erg{\"u}n, Inci and Zittel, Janina and Koch, Thorsten}, title = {Synergistic approach of multi-energy models for a European optimal energy system management tool}, series = {The Project Repository Journal}, volume = {9}, journal = {The Project Repository Journal}, pages = {113 -- 116}, language = {en} }