530. A tailored, matrix free interior point method for fast optimization on gas networks
Invited abstract in session WC-11: Interior point methods and applications - Part II, stream Interior point methods and applications.
Wednesday, 14:00-16:00Room: B100/5017
Authors (first author is the speaker)
| 1. | Rowan Turner
|
| University of Edinburgh | |
| 2. | Lars Schewe
|
| School of Mathematics, University of Edinburgh | |
| 3. | John Pearson
|
| School of Mathematics, University of Edinburgh |
Abstract
We consider a PDE-constrained optimization problem arising from the prospective use of hydrogen as an energy carrier to support fully renewable electric grids. One important question is whether existing natural gas infrastructure can be reused for hydrogen to this end, and the challenges this brings for the control of these networks. We expect that a hydrogen network which uses gas generated from excess renewable electricity would be more difficult to control as the patterns of injection and withdrawal would be much less regular than today. Additional challenges arise from new operating parameters required for hydrogen -- such as controlling for pressure fluctuations to prevent pipe-ageing. Motivated by a need for instationary optimization methods on networks at scale, we present a specialized, matrix free interior point method for gas problems. Our test problem is a line-pack optimization problem using a discretization of the 1d isothermal Euler equations, as a step towards understanding the important questions above. By incorporating a bespoke preconditioned iterative solver to tackle the linearized systems at each iteration of the interior point method, which form the key computational bottleneck in such a method, we utilize the highly structured nature of the problem to gain efficiency. The expectation is that the method will scale well with both network size and time windows, and be generalizable to broader PDE-constrained network optimization problems.
Keywords
- Optimal control and applications
- Computational linear algebra
- Optimization in industry, business and finance
Status: accepted
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