Refine
Document Type
- Article (8)
- ZIB-Report (4)
- Book chapter (1)
Is part of the Bibliography
- no (13)
Keywords
- Energiewende (1)
- Hydrogen Infrastructure (1)
- Hydrogen Transport (1)
- Mixed Integer Programming (1)
- Network Flows (1)
This article deals with the Jeep Problem (also known as Desert Crossing Problem), which reads as follows: An unlimited supply of fuel is available at one edge of a desert, but there is no source on the desert itself. A vehicle can carry enough fuel to go a certain distance, and it can built up its own refuelling stations. What is the minimum amount of fuel the vehicle will require in order to cross the desert? Under these mild conditions this question is answered since the 1940s. But what is the answer if the caches are restricted to certain areas or if the fuel consumption does not depend linearly on the distance travelled? To answer these and similar questions we develop and solve a flexible mixed-integer programming (MIP) model for the classical problem and enhance it with new further aspects of practical relevance.
This article answers two kinds of questions regarding the Bundesliga which is Germany's primary football (soccer) competition having the highest average stadium attendance worldwide. First "At any point of the season, what final rank will a certain team definitely reach?" and second "At any point of the season, what final rank can a certain team at most reach?". Although we focus especially on the Bundesliga, the models that we use to answer the two questions can easily be adopted to league systems that are similar to that of the Bundesliga.
Im BDEW/VKU/GEODE-Leitfaden Krisenvorsorge Gas ist zu lesen, dass als oberster Grundsatz zur Vermeidung von Versorgungsengpässen in Gasversorgungssystemen gilt, möglichst laufend einen Bilanzausgleich in allen Teilen des Netzes zu erreichen. Wir entwickeln Modelle zur Optimierung des laufenden Bilanzausgleichs. Als Gasversorgungssystem betrachten wir modellhaft die Fernleitungsnetze eines Marktgebiets. Als Teile des Gasversorgungssystems fassen wir vereinfachend die jeweiligen Netze der Fernleitungsnetzbetreiber auf. Die Optimierung erfolgt in zwei Schritten. Im ersten Schritt wird der optimale Einsatz netzbezogener Maßnahmen ermittelt. Beispiele für netzbezogene Maßnahmen sind die Nutzung von Netzpuffer und Mengenverlagerungen mit anderen Infrastrukturbetreibern. Falls sich die Bilanzen durch netzbezogene Maßnahmen nicht vollständig ausgleichen lassen, werden Fehlmengen angesetzt, die so gleichmäßig wie möglich auf die Teile des Netzes verteilt werden. Im zweiten Schritt werden die verbliebenen Fehlmengen, welche in der Regel durch marktbezogene Maßnahmen bereinigt werden, regulierungskonform auf möglichst große Teile des Gasversorgungssystems verteilt. Im Ergebnis erhalten wir ein transparentes, gerechtes, flexibel parametrier- und erweiterbares Verfahren, welches zyklisch im Dispatchingprozess eingesetzt werden kann, um die Integrität der Netze zu unterstützen. Dies wird an Beispielen verdeutlicht.
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.
In this paper, we describe an algorithmic framework for the optimal operation of transient gas transport networks consisting of a hierarchical MILP formulation together with a sequential linear programming inspired post-processing routine. Its implementation is part of the KOMPASS decision support system, which is currently used in an industrial setting.
Real-world gas transport networks are controlled by operating complex pipeline intersection areas, which comprise multiple compressor units, regulators, and valves. In the following, we introduce the concept of network stations to model them. Thereby, we represent the technical capabilities of a station by hand-tailored artificial arcs and add them to network. Furthermore, we choose from a predefined set of flow directions for each network station and time step, which determines where the gas enters and leaves the station. Additionally, we have to select a supported simple state, which consists of two subsets of artificial arcs: Arcs that must and arcs that cannot be used. The goal is to determine a stable control of the network satisfying all supplies and demands.
The pipeline intersections, that are represented by the network stations, were initially built centuries ago. Subsequently, due to updates, changes, and extensions, they evolved into highly complex and involved topologies. To extract their basic properties and to model them using computer-readable and optimizable descriptions took several years of effort.
To support the dispatchers in controlling the network, we need to compute a continuously updated list of recommended measures. Our motivation for the model presented here is to make fast decisions on important transient global control parameters, i.e., how to route the flow and where to compress the gas. Detailed continuous and discrete technical control measures realizing them, which take all hardware details into account, are determined in a subsequent step.
In this paper, we present computational results from the KOMPASS project using detailed real-world data.
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.
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.