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Computational Optimization of Gas Compressor Stations: MINLP Models vs. Continuous Reformulations

Daniel Rose(rose***at***ifam.uni-hannover.de)
Martin Schmidt(mar.schmidt***at***fau.de)
Marc C. Steinbach(mcs***at***ifam.uni-hannover.de)
Bernhard M. Willert(willert***at***ifam.uni-hannover.de)

Abstract: When considering cost-optimal operation of gas transport networks, compressor stations play the most important role. Proper modeling of these stations leads to complicated mixed-integer nonlinear and nonconvex optimization problems. In this article, we give an isothermal and stationary description of compressor stations, state MINLP and GDP models for operating a single station, and discuss several continuous reformulations of the problem. The applicability and relevance of different model formulations, especially of those without discrete variables, is demonstrated by a computational study on both academic examples and real-world stations.

Keywords: Discrete-continuous nonlinear optimization, Gas networks, Gas compressor stations, Mixed-integer optimization, Continuous reformulations

Category 1: Applications -- Science and Engineering

Category 2: Integer Programming ((Mixed) Integer Nonlinear Programming )

Category 3: Nonlinear Optimization

Citation:

Download: [PDF]

Entry Submitted: 02/26/2015
Entry Accepted: 02/26/2015
Entry Last Modified: 02/26/2015

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