@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} } @misc{PedersenHoppmannBaumZitteletal.2021, 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; Technical Report}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-82838}, year = {2021}, abstract = {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.}, language = {en} } @article{HoppmannBaum2021, author = {Hoppmann-Baum, Kai}, title = {On the Complexity of Computing Maximum and Minimum Min-Cost-Flows}, journal = {Networks}, doi = {10.1002/net.22060}, year = {2021}, abstract = {Consider a flow network, i.e., a directed graph where each arc has a nonnegative capacity value and an associated length, together with nonempty supply intervals for the sources and nonempty demand intervals for the sinks. The Maximum Min-Cost-Flow Problem (MaxMCF) is to find fixed supply and demand values within these intervals such that the optimal objective value of the induced Min-Cost-Flow Problem (MCF) is maximized. In this paper, we show that MaxMCF as well as its uncapacitated variant, the Maximum Transportation Problem (MaxTP), are NP-hard. Further, we prove that MaxMCF is APX-hard if a connectedness-condition regarding the sources and the sinks of the flow network is dropped. Finally, we show how the Minimum Min-Cost-Flow Problem (MinMCF) can be solved in polynomial time.}, language = {en} } @article{HenningsAndersonHoppmannBaumetal.2021, author = {Hennings, Felix and Anderson, Lovis and Hoppmann-Baum, Kai and Turner, Mark and Koch, Thorsten}, title = {Controlling transient gas flow in real-world pipeline intersection areas}, volume = {22}, journal = {Optimization and Engineering}, edition = {2}, publisher = {Springer Nature}, doi = {https://doi.org/10.1007/s11081-020-09559-y}, pages = {687 -- 734}, year = {2021}, abstract = {Compressor stations are the heart of every high-pressure gas transport network. Located at intersection areas of the network they are contained in huge complex plants, where they are in combination with valves and regulators responsible for routing and pushing the gas through the network. Due to their complexity and lack of data compressor stations are usually dealt with in the scientific literature in a highly simplified and idealized manner. As part of an ongoing project with one of Germany's largest Transmission System Operators to develop a decision support system for their dispatching center, we investigated how to automatize control of compressor stations. Each station has to be in a particular configuration, leading in combination with the other nearby elements to a discrete set of up to 2000 possible feasible operation modes in the intersection area. Since the desired performance of the station changes over time, the configuration of the station has to adapt. Our goal is to minimize the necessary changes in the overall operation modes and related elements over time, while fulfilling a preset performance envelope or demand scenario. This article describes the chosen model and the implemented mixed integer programming based algorithms to tackle this challenge. By presenting extensive computational results on real world data we demonstrate the performance of our approach.}, language = {en} } @phdthesis{HoppmannBaum2022, author = {Hoppmann-Baum, Kai}, title = {Mathematical programming for stable control and safe operation of gas transport networks}, publisher = {TU Berlin}, doi = {10.14279/depositonce-15837}, year = {2022}, abstract = {The fight against climate change makes extreme but inevitable changes in the energy sector necessary. These in turn lead to novel and complex challenges for the transmission system operators (TSOs) of gas transport networks. In this thesis, we consider four different planning problems emerging from real-world operations and present mathematical programming models and solution approaches for all of them. Due to regulatory requirements and side effects of renewable energy production, controlling today's gas networks with their involved topologies is becoming increasingly difficult. Based on the network station modeling concept for approximating the technical capabilities of complex subnetworks, e.g., compressor stations, we introduce a tri-level MIP model to determine important global control decisions. Its goal is to avoid changes in the network elements' settings while deviations from future inflow pressures as well as supplies and demands are minimized. A sequential linear programming inspired post-processing routine is run to derive physically accurate solutions w.r.t. the transient gas flow in pipelines. Computational experiments based on real-world data show that meaningful solutions are quickly and reliably determined. Therefore, the algorithmic approach is used within KOMPASS, a decision support system for the transient network control that we developed together with the Open Grid Europe GmbH (OGE), one of Europe's largest natural gas TSOs. Anticipating future use cases, we adapt the aforementioned algorithmic approach for hydrogen transport. We investigate whether the natural gas infrastructure can be repurposed and how the network control changes when energy-equivalent amounts of hydrogen are transported. Besides proving the need for purpose-built compressors, we observe that, due to the reduced linepack, the network control becomes more dynamic, compression energy increases by 440\% on average, and stricter regulatory rules regarding the balancing of supply and demand become necessary. Extreme load flows expose the technical limits of gas networks and are therefore of great importance to the TSOs. In this context, we introduce the Maximum Transportation Problem and the Maximum Potential Transport Moment Problem to determine severe transport scenarios. Both can be modeled as linear bilevel programs where the leader selects supplies and demands, maximizing the follower's transport effort. To solve them, we identify solution-equivalent instances with acyclic networks, provide variable bounds regarding their KKT reformulations, apply the big-M technique, and solve the resulting MIPs. A case study shows that the obtained scenarios exceed the maximum severity values of a provided test set by at least 23\%. OGE's transmission system is 11,540km long. Monitoring it is crucial for safe operations. To this end, we discuss the idea of using uncrewed aerial vehicles and introduce the Length-Constrained Cycle Partition Problem to optimize their routing. Its goal is to find a smallest cycle partition satisfying vertex-induced length requirements. Besides a greedy-style heuristic, we propose two MIP models. Combining them with symmetry-breaking constraints as well as valid inequalities and lower bounds from conflict hypergraphs yields a highly performant solution algorithm for this class of problems.}, language = {en} } @article{HenningsHoppmannBaumZittel2024, author = {Hennings, Felix and Hoppmann-Baum, Kai and Zittel, Janina}, title = {Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics}, volume = {5}, journal = {Open Journal of Mathematical Optimization}, arxiv = {http://arxiv.org/abs/2205.11369}, doi = {10.5802/ojmo.29}, pages = {34}, year = {2024}, language = {en} } @misc{PrauseHoppmannBaumDefournyetal.2020, author = {Prause, Felix and Hoppmann-Baum, Kai and Defourny, Boris and Koch, Thorsten}, title = {The Maximum Diversity Assortment Selection Problem}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-81039}, year = {2020}, abstract = {In this paper, we introduce the Maximum Diversity Assortment Selection Problem (MADASS), which is a generalization of the 2-dimensional Cutting Stock Problem (2CSP). Given a set of rectangles and a rectangular container, the goal of 2CSP is to determine a subset of rectangles that can be placed in the container without overlapping, i.e., a feasible assortment, such that a maximum area is covered. In MADASS, we need to determine a set of feasible assortments, each of them covering a certain minimum threshold of the container, such that the diversity among them is maximized. Thereby, diversity is defined as minimum or average normalized Hamming-Distance of all assortment pairs. The MADASS Problem was used in the 11th AIMMS-MOPTA Competition in 2019. The methods we describe in this article and the computational results won the contest. In the following, we give a definition of the problem, introduce a mathematical model and solution approaches, determine upper bounds on the diversity, and conclude with computational experiments conducted on test instances derived from the 2CSP literature.}, language = {en} } @article{HoppmannBaumHenningsZitteletal.2021, 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}, journal = {Mathematical Methods of Operations Research}, number = {Special Issue on Energy Networks}, year = {2021}, language = {en} } @misc{HoppmannBaumMexiBurdakovetal.2020, author = {Hoppmann-Baum, Kai and Mexi, Gioni and Burdakov, Oleg and Casselgren, Carl Johan and Koch, Thorsten}, title = {Length-Constrained Cycle Partition with an Application to UAV Routing}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-80489}, year = {2020}, abstract = {In this article, we discuss the Length-Constrained Cycle Partition Problem (LCCP). Besides edge weights, the undirected graph in LCCP features an individual critical weight value for each vertex. A cycle partition, i.e., a vertex disjoint cycle cover, is a feasible solution if the length of each cycle is not greater than the critical weight of each of the vertices in the cycle. The goal is to find a feasible partition with the minimum number of cycles. In this article, we discuss theoretical properties, preprocessing techniques, and two mixed-integer programming models (MIP) for LCCP both inspired by formulations for the closely related Travelling Salesperson Problem (TSP). Further, we introduce conflict hypergraphs, whose cliques yield valid constraints for the MIP models. We conclude with a report on computational experiments conducted on (A)TSPLIB-based instances. As an example, we use a routing problem in which a fleet of uncrewed aerial vehicles (UAVs) patrols a set of areas.}, language = {en} } @article{GotzesHoppmannBaum2020, author = {Gotzes, Uwe and Hoppmann-Baum, Kai}, title = {Bounding the final rank during a round robin tournament with integer programming}, volume = {1866-1505}, journal = {Operational Research}, doi = {https://doi.org/10.1007/s12351-020-00546-w}, year = {2020}, abstract = {This article is mainly motivated by the urge to answer two kinds of questions regarding the Bundesliga, which is Germany's primary football (soccer) division having the highest average stadium attendance worldwide: "At any point in the season, what is the lowest final rank a certain team can achieve?" and "At any point in the season, what is the highest final rank a certain team can achieve?". Although we focus on the Bundesliga in particular, the integer programming formulations we introduce to answer these questions can easily be adapted to a variety of other league systems and tournaments.}, language = {en} }