Details
| Original language | English |
|---|---|
| Pages (from-to) | 437-472 |
| Number of pages | 36 |
| Journal | Optimization and engineering |
| Volume | 17 |
| Issue number | 2 |
| Publication status | Published - 29 Dec 2015 |
Abstract
Due to strict regulatory rules in combination with complex nonlinear physics, major gas network operators in Germany and Europe face hard planning problems that call for optimization. In part 1 of this paper we have developed a suitable model hierarchy for that purpose. Here we consider the more practical aspects of modeling. We validate individual model components against a trusted simulation tool, give a structural overview of the model hierarchy, and use its large variety of approximations to devise robust and efficient solution techniques. An extensive computational study demonstrates the suitability of our models and techniques for previously unsolvable problems in gas network planning.
Keywords
- Gas networks, High-detail modeling, Model validation, Sequential NLP solving, Stationary operation
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Mathematics(all)
- Control and Optimization
- Engineering(all)
- Electrical and Electronic Engineering
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In: Optimization and engineering, Vol. 17, No. 2, 29.12.2015, p. 437-472.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - High detail stationary optimization models for gas networks
T2 - validation and results
AU - Schmidt, Martin
AU - Steinbach, Marc C.
AU - Willert, Bernhard M.
N1 - Funding Information: This work has been supported by the German Federal Ministry of Economics and Technology owing to a decision of the German Bundestag. The responsibility for the content of this publication lies with the authors. This research has been performed as part of the Energie Campus Nürnberg and supported by funding through the “Aufbruch Bayern (Bavaria on the move)” initiative of the state of Bavaria. We would also like to thank our industry partner Open Grid Europe GmbH and the project partners in the ForNe consortium. Finally, we thank Björn Geißler and Antonio Morsi for many suggestions for improvement.
PY - 2015/12/29
Y1 - 2015/12/29
N2 - Due to strict regulatory rules in combination with complex nonlinear physics, major gas network operators in Germany and Europe face hard planning problems that call for optimization. In part 1 of this paper we have developed a suitable model hierarchy for that purpose. Here we consider the more practical aspects of modeling. We validate individual model components against a trusted simulation tool, give a structural overview of the model hierarchy, and use its large variety of approximations to devise robust and efficient solution techniques. An extensive computational study demonstrates the suitability of our models and techniques for previously unsolvable problems in gas network planning.
AB - Due to strict regulatory rules in combination with complex nonlinear physics, major gas network operators in Germany and Europe face hard planning problems that call for optimization. In part 1 of this paper we have developed a suitable model hierarchy for that purpose. Here we consider the more practical aspects of modeling. We validate individual model components against a trusted simulation tool, give a structural overview of the model hierarchy, and use its large variety of approximations to devise robust and efficient solution techniques. An extensive computational study demonstrates the suitability of our models and techniques for previously unsolvable problems in gas network planning.
KW - Gas networks
KW - High-detail modeling
KW - Model validation
KW - Sequential NLP solving
KW - Stationary operation
UR - http://www.scopus.com/inward/record.url?scp=84951919756&partnerID=8YFLogxK
U2 - 10.1007/s11081-015-9300-3
DO - 10.1007/s11081-015-9300-3
M3 - Article
AN - SCOPUS:84951919756
VL - 17
SP - 437
EP - 472
JO - Optimization and engineering
JF - Optimization and engineering
SN - 1389-4420
IS - 2
ER -