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In this paper we give an analytical description on the structure of
solutions to the gas nomination validation problem in gas
transportation networks. These networks are assumed to contain no
active devices, only certain hypothetical pipelines, where the flow
of gas is modeled by a generalized version of the quadratic
Weymouth's equation. The purpose of considering generalized flow
formulas is to be able to adapt our results to various gas network
optimization problems involving gas flow formulas beyond Weymouth's
equation. Such formulas can appear in leaves of branch and bound
trees, or they can stem from discretization and linearization
carried out at active devices. We call a balanced supply-demand
vector a nomination, and the passive nomination validation problem
is to decide whether there exist pressures at the nodes generating a
given nomination. We prove that in our setup the pressure square
vectors generating a given nomination form a one-dimensional
connected and continuous curve in the pressure square space, and
this curve is a line for the classical Weymouth's equation. We also
present a visual approach for the easy comprehension of how this
solution curve arises; we give a short investigation of the set of
feasible nominations; and finally we give a proof that the
nomination validation problem in gas networks with active devices is
NP-complete.

Gas distribution networks are complex structures that consist of
passive pipes, and active, controllable elements such as valves and
compressors. Controlling such network means to find a suitable setting
for all active components such that a nominated amount of gas can be
transmitted from entries to exits through the network, without
violating physical or operational constraints. The control of a
large-scale gas network is a challenging task from a practical point
of view. In most companies the actual controlling process is supported
by means of computer software that is able to simulate the flow of the
gas. However, the active settings have to be set manually within such
simulation software. The solution quality thus depends on the
experience of a human planner.
When the gas network is insufficient for the transport then topology
extensions come into play. Here a set of new pipes or active elements
is determined such that the extended network admits a feasible control
again. The question again is how to select these extensions and where
to place them such that the total extension costs are
minimal. Industrial practice is again to use the same simulation
software, determine extensions by experience, add them to the virtual
network, and then try to find a feasible control of the active
elements. The validity of this approach now depends even more on the
human planner.
Another weakness of this manual simulation-based approach is that it
cannot establish infeasibility of a certain gas nomination, unless all
settings of the active elements are tried. Moreover, it is impossible
to find a cost-optimal network extension in this way.
In order to overcome these shortcomings of the manual planning
approach we present a new approach, rigorously based on mathematical
optimization. Hereto we describe a model for finding feasible
controls and then extend this model such that topology extensions can
additionally and simultaneously be covered. Numerical results for real-world instances are presented and
discussed.