Multi-period stochastic network design for combined natural gas and hydrogen distribution
Umur Hasturk et al.
Abstract
Hydrogen is produced from water using renewable electricity. Unlike electricity, hydrogen can be stored in large quantities for long periods. This storage ability acts as a green battery , allowing solar and wind energy to be generated and used at different times. As a result, green hydrogen plays a central role in facilitating a climate-neutral economy. However, the logistics for hydrogen are complex. As new pipelines are developed for hydrogen, there is a trend toward repurposing the natural gas network for hydrogen, due to its economic and environmental benefits. Yet, a rapid conversion could disrupt the balance of natural gas supply and demand. Furthermore, technical and economic developments surrounding the transition contribute additional complexity, which introduces uncertainty in future supply and demand levels for both commodities. To address these challenges, we introduce a multi-period stochastic network design problem for the transition of a natural gas pipeline network into a green hydrogen pipeline network. We develop a progressive-hedging-based metaheuristic to solve the problem. Results demonstrate our matheuristic is efficient, both in computation time and in solution quality. We show that factoring in uncertainty avoids premature expansion and ensures the development of an adequate pipeline network meeting long-term needs. In a case study in the Northern Netherlands for Hydrogen Energy Applications in Valley Environments for Northern Netherlands initiative, we focus on two key scenarios: local production and importation, exploring their impacts on performance indicators. Our case insights exemplify the solid foundation for strategic decision-making in energy transitions through our approach. • Hydrogen’s versatility drives network design challenges in energy transitions. • Multi-period stochastic model integrates network design, pipeline flow, storage and inventory decisions. • Progressive-hedging-based matheuristic ensures high solution quality. • Case study in Northern Netherlands highlights pipeline retrofitting strategies.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.