Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks

Hante F, Schmidt M (2017)

Publication Language: English

Publication Type: Other publication type

Publication year: 2017

URI: http://www.optimization-online.org/DB_HTML/2017/09/6198.html

Abstract

We consider nonlinear and nonsmooth mixing aspects in gas transport optimization problems. As mixed-integer reformulations of pooling-type mixing models already render small-size instances computationally intractable, we investigate the applicability of smooth nonlinear programming techniques for equivalent complementarity-based reformulations. Based on recent results for remodeling piecewise affine constraints using an inverse parametric quadratic programming approach, we show that classical stationarity concepts are meaningful for the resulting complementarity-based reformulation of the mixing equations. Further, we investigate in a numerical study the performance of this reformulation compared to a more compact complementarity-based one that does not feature such beneficial regularity properties. All computations are performed on publicly available data of real-world size problem instances from steady-state gas transport.

Authors with CRIS profile

Falk Hante Lehrstuhl für Angewandte Mathematik Martin Schmidt Juniorprofessur für Optimierung von Energiesystemen

Related research project(s)

Energiemarktdesign (EMD) Energie Campus Nürnberg (EnCN2) Jan. 1, 2017 - Dec. 31, 2021 Welfare optimal nominations in gas networks and associated equilibria SFB TRR 154 “Mathematische Modellierung, Simulation und Optimierung am Beispiel von Gasnetzen” Oct. 1, 2016 - June 30, 2018

How to cite

APA:

Hante, F., & Schmidt, M. (2017). Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks.

MLA:

Hante, Falk, and Martin Schmidt. Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks. 2017.

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