TY - GEN A1 - Yueksel-Erguen, Inci A1 - Zittel, Janina A1 - Wang, Ying A1 - Hennings, Felix A1 - Koch, Thorsten T1 - Lessons learned from gas network data preprocessing N2 - The German high-pressure natural gas transport network consists of thousands of interconnected elements spread over more than 120,000 km of pipelines built during the last 100 years. During the last decade, we have spent many person-years to extract consistent data out of the available sources, both public and private. Based on two case studies, we present some of the challenges we encountered. Preparing consistent, high-quality data is surprisingly hard, and the effort necessary can hardly be overestimated. Thus, it is particularly important to decide which strategy regarding data curation to adopt. Which precision of the data is necessary? When is it more efficient to work with data that is just sufficiently correct on average? In the case studies we describe our experiences and the strategies we adopted to deal with the obstacles and to minimize future effort. Finally, we would like to emphasize that well-compiled data sets, publicly available for research purposes, provide the grounds for building innovative algorithmic solutions to the challenges of the future. T3 - ZIB-Report - 20-13 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-78262 SN - 1438-0064 ER - TY - GEN A1 - Petkovic, Milena A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Deep learning for spatio-temporal supply and demand forecasting in natural gas transmission networks 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. T3 - ZIB-Report - 21-01 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-81221 SN - 1438-0064 ER - TY - JOUR A1 - Hoppmann-Baum, Kai A1 - Hennings, Felix A1 - Zittel, Janina A1 - Gotzes, Uwe A1 - Spreckelsen, Eva-Maria A1 - Spreckelsen, Klaus A1 - Koch, Thorsten T1 - An Optimization Approach for the Transient Control of Hydrogen Transport Networks JF - Mathematical Methods of Operations Research Y1 - 2021 IS - Special Issue on Energy Networks ER - TY - GEN A1 - Hoppmann-Baum, Kai A1 - Hennings, Felix A1 - Zittel, Janina A1 - Gotzes, Uwe A1 - Spreckelsen, Eva-Maria A1 - Spreckelsen, Klaus A1 - Koch, Thorsten T1 - From Natural Gas towards Hydrogen - A Feasibility Study on Current Transport Network Infrastructure and its Technical Control N2 - This study examines the usability of a real-world, large-scale natural gas transport infrastructure for hydrogen transport. We investigate whether a converted network can transport the amounts of hydrogen necessary to satisfy current energy demands. After introducing an optimization model for the robust transient control of hydrogen networks, we conduct computational experiments based on real-world demand scenarios. Using a representative network, we demonstrate that replacing each turbo compressor unit by four parallel hydrogen compressors, each of them comprising multiple serial compression stages, and imposing stricter rules regarding the balancing of in- and outflow suffices to realize transport in a majority of scenarios. However, due to the reduced linepack there is an increased need for technical and non-technical measures leading to a more dynamic network control. Furthermore, the amount of energy needed for compression increases by 364% on average. T3 - ZIB-Report - 20-27 KW - Hydrogen Transport KW - Hydrogen Infrastructure KW - Network Flows KW - Mixed Integer Programming KW - Energiewende Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-79901 SN - 1438-0064 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 - JOUR A1 - Petkovic, Milena A1 - Chen, Ying A1 - Gamrath, Inken A1 - Gotzes, Uwe A1 - Hadjidimitrou, Natalia Selini A1 - Zittel, Janina A1 - Xu, Xiaofei A1 - Koch, Thorsten T1 - A hybrid approach for high precision prediction of gas flows JF - Energy Systems N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1007/s12667-021-00466-4 VL - 13 SP - 383 EP - 408 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 - Zakiyeva, Nazgul A1 - Zittel, Janina T1 - Statistical analysis and modeling for detecting regime changes in gas nomination time series 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 hours ahead. In our study, we aim to investigate the regime changes in the time series of nominations to predict the 6 to 10 hours ahead of gas nominations. T3 - ZIB-Report - 21-22 KW - Time series Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-82988 SN - 1438-0064 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 - 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 - GEN A1 - Hennings, Felix A1 - Hoppmann-Baum, Kai A1 - Zittel, Janina T1 - Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics N2 - Optimizing the transient control of gas networks is a highly challenging task. The corresponding model incorporates the combinatorial complexity of determining the settings for the many active elements as well as the non-linear and non-convex nature of the physical and technical principles of gas transport. In this paper, we present the latest improvements of our ongoing work to solve this problem for real-world, large-scale problem instances: By adjusting our mixed-integer non-linear programming model regarding the gas compression capabilities in the network, we reflect the technical limits of the underlying units more accurately while maintaining a similar overall model size. In addition, we introduce a new algorithmic approach that is based on splitting the complexity of the problem by first finding assignments for discrete variables and then determining the continuous variables as locally optimal solution of the corresponding non-linear program. For the first task, we design multiple different heuristics based on concepts for general time-expanded optimization problems that find solutions by solving a sequence of sub-problems defined on reduced time horizons. To demonstrate the competitiveness of our approach, we test our algorithm on particularly challenging historic demand scenarios. The results show that high-quality solutions are obtained reliably within short solving times, making the algorithm well-suited to be applied at the core of time-critical industrial applications. T3 - ZIB-Report - 22-08 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-86842 SN - 1438-0064 ER - TY - GEN A1 - Yueksel-Erguen, Inci A1 - Most, Dieter A1 - Wyrwoll, Lothar A1 - Schmitt, Carlo A1 - Zittel, Janina T1 - Modeling the transition of the multimodal pan-European energy system including an integrated analysis of electricity and gas transport N2 - The European energy system has been through a fundamental transformation since the Paris Agreement to reduce greenhouse gas emissions. The transition involves several energy-generating and consuming sectors emphasizing sector coupling. The increase in the share of renewable energy sources has revealed the need for flexibility in the electri city grid. Thus, holistic planning of pathways towards decarbonized energy systems also involves assessing the gas infrastructure to provide such a flexibility and support for the security of supply. In this paper, we propose a workflow to investigate such optimal energy transition pathways considering sector coupling. This workflow involves an integrated operational analysis of the electricity market, its transmission grid, and the gas grid in high spatio-temporal resolution. In a case study on a pan-European scale between 2020-2050, we show that carbon neutrality can be reached within feasible additional costs and in time. However, the manifestation of the potential pathways strongly depends on political and technological constraints. Sector coupling acts as an enabler of cross-border cooperation to achieve both, decarbonization and security of supply. T3 - ZIB-Report - 22-17 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-87774 SN - 1438-0064 ER - TY - GEN A1 - Pedersen, Jaap A1 - Le, Thi Thai A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Optimal discrete pipe sizing for tree-shaped CO2 networks N2 - While energy-intensive industries like the steel industry plan to switch to renewable energy sources, other industries, such as the cement industry, have to rely on carbon capture storage and utilization technologies to reduce the inevitable carbon dioxide (CO2) emissions of their production processes. 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 a challenging mixed-integer nonlinear program. Additionally, the behaviour of CO2 is highly sensitive and nonlinear 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 modelling including mixing effects, the Joule-Thomson effect, and heat exchange with the surrounding environment. We show the effectiveness of our approach by applying our algorithm to a real-world network planning problem for a CO2 network in Western Germany. T3 - ZIB-Report - 22-15 KW - CO2 Transport KW - Network Design KW - Pipeline Sizing Y1 - 2022 SN - 1438-0064 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 - 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 - 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 - GEN A1 - Charousset-Brignol, Sandrine A1 - van Ackooij, Wim A1 - Oudjane, Nadia A1 - Daniel, Dominique A1 - Noceir, Slimane A1 - Haus, Utz-Uwe A1 - Lazzaro, Alfio A1 - Frangioni, Antonio A1 - Lobato, Rafael A1 - Ghezelsoflu, Ali A1 - Iardella, Niccolò A1 - Galli, Laura A1 - Gorgone, Enrico A1 - dell’Amico, Mauro A1 - Giannelos, Spyros A1 - Moreira, Alex A1 - Strbac, Goran A1 - Borozan, Stefan A1 - Falugi, Paula A1 - Pudjianto, Danny A1 - Wyrwoll, Lothar A1 - Schmitt, Carlo A1 - Franken, Marco A1 - Beulertz, Daniel A1 - Schwaeppe, Henrik A1 - Most, Dieter A1 - Yüksel-Ergün, Inci A1 - Zittel, Janina A1 - Koch, Thorsten T1 - Synergistic approach of multi-energy models for a European optimal energy system management tool T2 - The Project Repository Journal Y1 - 2021 VL - 9 SP - 113 EP - 116 ER - TY - GEN A1 - Clarner, Jan-Patrick A1 - Tawfik, Christine A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Network-induced Unit Commitment - A model class for investment and production portfolio planning for multi-energy systems N2 - In light of the energy transition production planning of future decarbonized energy systems lead to very large and complex optimization problems. A widely used modeling paradigm for modeling and solving such problems is mathematical programming. While there are various scientific energy system models and modeling tools, most of them do not provide the necessary level of detail or the modeling flexibility to be applicable for industrial usage. Industrial modeling tools, on the other hand, provide a high level of detail and modeling flexibility. However, those models often exhibit a size and complexity that restricts their scope to a time horizon of several months, severely complicating long-term planning. As a remedy, we propose a model class that is detailed enough for real-world usage but still compact enough for long-term planning. The model class is based on a generalized unit commitment problem on a network with investment decisions. The focus lies on the topological dependency of different energy production and transportation units. T3 - ZIB-Report - 22-16 KW - Multi-energy systems KW - Unit commitment KW - Investment planning Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-87607 SN - 1438-0064 ER - TY - JOUR A1 - Yueksel-Erguen, Inci A1 - Most, Dieter A1 - Wyrwoll, Lothar A1 - Schmitt, Carlo A1 - Zittel, Janina T1 - Modeling the transition of the multimodal pan-European energy system including an integrated analysis of electricity and gas transport JF - Energy Systems N2 - Most recently, the European energy system has undergone a fundamental transformation to meet decarbonization targets without compromising the security of the energy supply. The transition involves several energy-generating and consuming sectors emphasizing sector coupling. The increase in the share of renewable energy sources has revealed the need for flexibility in supporting the electricity grid to cope with the resulting high degree of uncertainty. The new technologies accompanying the energy system transition and the recent political crisis in Europe threatening the security of the energy supply have invalidated the experience from the past by drastically changing the conventional scenarios. Hence, supporting strategic planning tools with detailed operational energy network models with appropriate mathematical precision has become more important than ever to understand the impacts of these disruptive changes. In this paper, we propose a workflow to investigate optimal energy transition pathways considering sector coupling. This workflow involves an integrated operational analysis of the electricity market, its transmission grid, and the gas grid in high spatio-temporal resolution. Thus, the workflow enables decision-makers to evaluate the reliability of high-level models even in case of disruptive events. We demonstrate the capabilities of the proposed workflow using results from a pan-European case study. The case study, spanning 2020-2050, illustrates that feasible potential pathways to carbon neutrality are heavily influenced by political and technological constraints. Through integrated operational analysis, we identify scenarios where strategic decisions become costly or infeasible given the existing electricity and gas networks. Y1 - 2023 U6 - https://doi.org/10.1007/s12667-023-00637-5 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 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 - 2023 ER - TY - CHAP A1 - Petkovic, Milena A1 - Zittel, Janina T1 - Forecasting and modeling the dynamics of large-scale energy networks under the supply and demand balance constraint T2 - AIRO Springer Series: International Conference on Optimization and Decision Science N2 - With the emergence of ”Big Data” the analysis of large data sets of high-dimensional energy time series in network structures have become feasible. However, building large-scale data-driven and computationally efficient models to accurately capture the underlying spatial and temporal dynamics and forecast the multivariate time series data remains a great challenge. Additional constraints make the problem more challenging to solve with conventional methods. For example, to ensure the security of supply, energy networks require the demand and supply to be balanced. This paper introduces a novel large-scale Hierarchical Network Regression model with Relaxed Balance constraint (HNR-RB) to investigate the network dynamics and predict multistep-ahead flows in the natural gas transmission network, where the total in- and out-flows of the network have to be balanced over a period of time. We concurrently address three main challenges: high dimensionality of networks with more than 100 nodes, unknown network dynamics, and constraint of balanced supply and demand in the network. The effectiveness of the proposed model is demonstrated through a real-world case study of forecasting demand and supply in a large-scale natural gas transmission network. The results demonstrate that HNR-RB outperforms alternative models for short- and mid-term horizons. Y1 - 2023 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 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 - 2023 ER - TY - JOUR A1 - Hennings, Felix A1 - Hoppmann-Baum, Kai A1 - Zittel, Janina T1 - Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics JF - Open Journal of Mathematical Optimization Y1 - 2024 ER - TY - GEN A1 - Cao, Karl-Kien A1 - Anderson, Lovis A1 - Böhme, Aileen A1 - Breuer, Thomas A1 - Buschmann, Jan A1 - Fiand, Frederick A1 - Frey, Ulrich A1 - Fuchs, Benjamin A1 - Kempe, Nils-Christian A1 - von Krbek, Kai A1 - Medjroubi, Wided A1 - Riehm, Judith A1 - Sasanpour, Shima A1 - Simon, Sonja A1 - Vanaret, Charlie A1 - Wetzel, Manuel A1 - Xiao, Mengzhu A1 - Zittel, Janina T1 - Evaluation of Uncertainties in Linear-Optimizing Energy System Models - Compendium T2 - DLR-Forschungsbericht N2 - Für die Energiesystemforschung sind Software-Modelle ein Kernelement zur Analyse von Szenarien. Das Forschungsprojekt UNSEEN hatte das Ziel eine bisher unerreichte Anzahl an modellbasierten Energieszenarien zu berechnen, um Unsicherheiten – vor allem unter Nutzung linear optimierender Energiesystem-Modelle - besser bewerten zu können. Hierfür wurden umfangreiche Parametervariationen auf Energieszenarien angewendet und das wesentliche methodische Hindernis in diesem Zusammenhang adressiert: die rechnerische Beherrschbarkeit der zu lösenden mathematischen Optimierungsprobleme. Im Vorläuferprojekt BEAM-ME wurde mit der Entwicklung und Anwendung des Open-Source-Lösers PIPS-IPM++ die Grundlage für den Einsatz von High-Performance-Computing (HPC) zur Lösung dieser Modelle gelegt. In UNSEEN war dieser Löser die zentrale Komponente eines Workflows, welcher zur Generierung, Lösung und multi-kriteriellen Bewertung von Energieszenarien auf dem Hochleistungscomputer JUWELS am Forschungszentrum Jülich implementiert wurde. Zur effizienten Generierung und Kommunikation von Modellinstanzen für Methoden der mathematischen Optimierung auf HPC wurde eine weitere Workflow-Komponente von der GAMS Software GmbH entwickelt: der Szenariogenerator. Bei der Weiterentwicklung von Lösungsalgorithmen für linear optimierende Energie-Systemmodelle standen gemischt-ganzzahlige Optimierungsprobleme im Fokus, welche für die Modellierung konkreter Infrastrukturen und Maßnahmen zur Umsetzung der Energiewende gelöst werden müssen. Die in diesem Zusammenhang stehenden Arbeiten zur Entwicklung von Algorithmen wurden von der Technischen Universität Berlin verantwortet. Bei Design und Implementierung dieser Methoden wurde sie vom Zuse Instituts Berlin unterstützt. Y1 - 2023 U6 - https://doi.org/10.57676/w2rq-bj85 IS - DLR-FB-2023-15 ER - TY - GEN A1 - Yueksel-Erguen, Inci A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Mathematical optimization based flow scenario generation for operational analysis of European gas transport networks based on open data N2 - The decarbonization of the European energy system demands a rapid and comprehensive transformation while securing energy supplies at all times. Still, natural gas plays a crucial role in this process. Recent unexpected events forced drastic changes in gas routes throughout Europe. Therefore, operational-level analysis of the gas transport networks and technical capacities to cope with these transitions using unconventional scenarios has become essential. Unfortunately, data limitations often hinder such analyses. To overcome this challenge, we propose a mathematical model-based scenario generator that enables operational analysis of the European gas network using open data. Our approach focuses on the consistent analysis of specific partitions of the gas transport network, whose network topology data is readily available. We generate reproducible and consistent node-based gas in/out-flow scenarios for these defined network partitions to enable feasibility analysis and data quality assessment. Our proposed method is demonstrated through several applications that address the feasibility analysis and data quality assessment of the German gas transport network. By using open data and a mathematical modeling approach, our method allows for a more comprehensive understanding of the gas transport network's behavior and assists in decision-making during the transition to decarbonization. T3 - ZIB-Report - 24-03 Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-95789 SN - 1438-0064 ER -