@inproceedings{HadjidimitriouLippiNastroetal.2024, author = {Hadjidimitriou, Natalia Selini and Lippi, Marco and Nastro, Raffaele and Koch, Thorsten and Mamei, Marco}, title = {Short-Term Forecasting of Energy Consumption and Production in Local Energy Communities}, booktitle = {2024 32nd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)}, publisher = {IEEE}, doi = {10.1109/WETICE64632.2024.00022}, pages = {74 -- 79}, year = {2024}, language = {en} } @article{RehfeldtKoch2023, author = {Rehfeldt, Daniel and Koch, Thorsten}, title = {Implications, Conflicts, and Reductions for Steiner Trees}, volume = {197}, journal = {Mathematical Programming}, publisher = {Springer}, doi = {10.1007/s10107-021-01757-5}, pages = {903 -- 966}, year = {2023}, language = {en} } @misc{KempkeRehfeldtKoch2024, author = {Kempke, Nils-Christian and Rehfeldt, Daniel and Koch, Thorsten}, title = {A Massively Parallel Interior-Point-Method for Arrowhead Linear Programs}, issn = {1438-0064}, arxiv = {http://arxiv.org/abs/2412.07731}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-98829}, year = {2024}, abstract = {In practice, non-specialized interior point algorithms often cannot utilize the massively parallel compute resources offered by modern many- and multi-core compute platforms. However, efficient distributed solution techniques are required, especially for large-scale linear programs. This article describes a new decomposition technique for systems of linear equations implemented in the parallel interior-point solver PIPS-IPM++. The algorithm exploits a matrix structure commonly found in optimization problems: a doubly-bordered block-diagonal or arrowhead structure. This structure is preserved in the linear KKT systems solved during each iteration of the interior-point method. We present a hierarchical Schur complement decomposition that distributes and solves the linear optimization problem; it is designed for high-performance architectures and scales well with the availability of additional computing resources. The decomposition approach uses the border constraints' locality to decouple the factorization process. Our approach is motivated by large-scale unit-commitment problems. We demonstrate the performance of our method on a set of mid-to large-scale instances, some of which have more than 10^9 nonzeros in their constraint matrix.}, language = {en} } @article{AbbasAmbainisAugustinoetal.2024, author = {Abbas, Amira and Ambainis, Andris and Augustino, Brandon and B{\"a}rtschi, Andreas and Buhrman, Harry and Coffrin, Carleton and Cortiana, Giorgio and Dunjko, Vedran and Egger, Daniel J. and Elmegreen, Bruce G. and Franco, Nicola and Fratini, Filippo and Fuller, Bryce and Gacon, Julien and Gonciulea, Constantin and Gribling, Sander and Gupta, Swati and Hadfield, Stuart and Heese, Raoul and Kircher, Gerhard and Kleinert, Thomas and Koch, Thorsten and Korpas, Georgios and Lenk, Steve and Marecek, Jakub and Markov, Vanio and Mazzola, Guglielmo and Mensa, Stefano and Mohseni, Naeimeh and Nannicini, Giacomo and O'Meara, Corey and Tapia, Elena Pe{\~n}a and Pokutta, Sebastian and Proissl, Manuel and Rebentrost, Patrick and Sahin, Emre and Symons, Benjamin C. B. and Tornow, Sabine and Valls, V{\´i}ctor and Woerner, Stefan and Wolf-Bauwens, Mira L. and Yard, Jon and Yarkoni, Sheir and Zechiel, Dirk and Zhuk, Sergiy and Zoufal, Christa}, title = {Challenges and opportunities in quantum optimization}, volume = {6}, journal = {Nature Reviews Physics}, publisher = {Springer Science and Business Media LLC}, issn = {2522-5820}, arxiv = {http://arxiv.org/abs/2312.02279}, doi = {10.1038/s42254-024-00770-9}, pages = {718 -- 735}, year = {2024}, language = {en} } @misc{VuKochXu2024, author = {Vu, Thi Huong and Koch, Thorsten and Xu, Hong-Kun}, title = {The gradient projection method: Is the Polyak adaptive stepsize rule optimal?}, year = {2024}, abstract = {Not always! This is our answer to the question of whether the Polyak adaptive stepsize rule in the gradient projection method is optimal. The answer is based on revisiting the subgradient projection method by Polyak [USSR Computational Mathematics and Mathematical Physics 9 (1969)] for smooth and convex minimization problems where the objective function possesses a geometric property called flatness. Our results show that the method can be more flexible (the effective range for the parameter controlling the stepsize can be wider) and have sharper convergence rates. Applications to split feasibility/equality problems are presented, deriving for the first time the O(1/k) rate of convergence for the adaptive CQ method. A theoretical guarantee of the linear convergence of the gradient descent method with adaptive stepsizes for Google PageRank is provided. At the same time, numerical experiments are designed to spot the ``optimal" stepsize and to compare with other basic gradient methods.}, language = {en} } @inproceedings{HadjidimitriouKochLippietal.2024, author = {Hadjidimitriou, Natalia Selini and Koch, Thorsten and Lippi, Marco and Petkovic, Milena and Mamei, Marco}, title = {Analysis of the Impact of COVID-19 and Russo-Ukraine War on Natural Gas Flow Using Time Series Forecasting}, booktitle = {Preceedings of the 16th International Conference on Management of Digital Ecosystems}, year = {2024}, language = {en} } @article{PedersenLeKochetal.2024, author = {Pedersen, Jaap and Le, Thi Thai and Koch, Thorsten and Zittel, Janina}, title = {Optimal discrete pipe sizing for tree-shaped CO2 networks}, volume = {46}, journal = {OR Spectrum}, doi = {10.1007/s00291-024-00773-z}, pages = {1163 -- 1187}, year = {2024}, 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} } @misc{YuekselErguenKochZittel2024, author = {Yueksel-Erguen, Inci and Koch, Thorsten and Zittel, Janina}, title = {Mathematical optimization based flow scenario generation for operational analysis of European gas transport networks based on open data}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-95789}, year = {2024}, abstract = {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.}, language = {en} } @article{PetkovicChenGamrathetal.2022, 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}, volume = {13}, journal = {Energy Systems}, doi = {10.1007/s12667-021-00466-4}, pages = {383 -- 408}, year = {2022}, 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} } @inproceedings{PedersenHoppmannBaumZitteletal.2022, 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}, booktitle = {Operations Research Proceedings 2021}, doi = {https://doi.org/10.1007/978-3-031-08623-6_28}, pages = {182 -- 187}, year = {2022}, 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} }