GasLib—A Library of Gas Network Instances

Abstract

Abstract:The development of mathematical simulation and optimization models and algorithms for solving gas transport problems is an active field of research. In order to test and compare these models and algorithms, gas network instances together with demand data are needed. The goal of GasLib is to provide a set of publicly available gas network instances that can be used by researchers in the field of gas transport. The advantages are that researchers save time by using these instances and that different models and algorithms can be compared on the same specified test sets. The library instances are encoded in an XML (extensible markup language) format. In this paper, we explain this format and present the instances that are available in the library.Data Set: http://gaslib.zib.de Data Set License: CC BY 3.0 Keywords: gas transport; networks; problem instances; mixed-integer nonlinear optimization; GasLib MSC: 90-08; 90C90; 90B10 SummaryThe mathematical simulation and optimization of gas transport through pipeline systems is an important field of research with a large practical impact. Over the last decades, many different mathematical models on different levels of accuracy for different components of gas networks have been developed. On the basis of these models, several simulation and optimization algorithms have been proposed. We refer to [1][2][3] and the references therein for more information. With GasLib, we provide a set of network instances that can be used to test and compare such models and the algorithms for solving them.

Optimal Inflow Control Penalizing Undersupply in Transport Systems with Uncertain Demands

“…Furthermore, we impose a JCC on the interval I CC = [0, 4]. We consider a discretization of dt = 60[s] and dx ≈ 1[km], again slightly adapted to the individual length of the edges, applied to the same subgrid of the GasLib-40 network [40] as above. Note that this coarse discretization is possible due to the chosen numerical scheme, the IBOX scheme (2).…”

Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach

“…Numerical setting Table 2 provides summary statistics for all networks. We test the traditional Belgian network from a previous study (De Wolf & Smeers, 2000), the German networks from the open data set GasLib (Schmidt et al, 2017), and Chinese networks of various sizes provided by CNPC. For each network, we implement all four methods: IPLA-De, IPLA-Ba, IPLA-New, and 3SCR.…”

Algorithmic results for potential‐based flows: Easy and hard cases

“…Finally, we discuss the results of our network reduction techniques applied to three small‐scale to medium‐scale academic, but realistic gas networks and two large‐scale real‐world gas networks. The academic networks are freely available online (see Schmidt et al ) and the real‐world instances are the low‐calorific and high‐calorific gas networks of the German gas transport company Open Grid Europe GmbH…”

“…On average, these nonconvex MINLPs have 2187 variables and 3733 constraints. We used the standard models provided by the GasLib , which all are feasibility problems. BARON is able to solve 2 out of the 10 unreduced instances.…”

“…Finally, we discuss the results of our network reduction techniques applied to three small-scale to medium-scale academic, but realistic gas networks and two large-scale real-world gas networks. The academic networks are freely available online (see Schmidt et al [40]) and the real-world instances are the low-calorific and high-calorific gas networks of the German gas transport company Open Grid Europe GmbH. 1 In contrast to the water and power network instances considered so far, the gas networks that we consider here contain active elements like valves (switches) to block gas flow, control valves to reduce gas pressure, and compressor stations that are used to increase gas pressure.…”