Fast optimization methods for the design and control of hydrogen gas networks

The usage of hydrogen gas as an energy carrier is one likely factor towards achieving a net zero future.

One important question is whether existing natural gas infrastructure can be re-used for hydrogen and the challenges this brings for the control of these future networks.

Motivated by a need for instationary optimization methods on networks at scale in order to answer this question on realistically sized networks and over useful time windows, this project works to develop a specialized interior point method (IPM) for gas problems.

Starting with a line-pack optimization problem using a discretization of the 1d isothermal Euler equations, the IPM incorporates a bespoke preconditioned iterative solver to tackle the linearized systems at each iteration of the IPM, which form the key computational bottleneck in such a method.

This utilizes the highly structured nature of the problem, which arises from both the network structure itself and the time discretization.

The expectation is that the method will scale well with both network size and time windows, and be generalizable to broader instationary gas network optimization problems.