EconPapers    
Economics at your fingertips  
 

Multistage stochastic optimization of a mono-site hydrogen infrastructure by decomposition techniques

Raian Lefgoum (), Sezin Afsar (), Pierre Carpentier (), Jean-Philippe Chancelier () and Michel De Lara ()
Additional contact information
Raian Lefgoum: IP Paris
Sezin Afsar: Universidad de Oviedo
Pierre Carpentier: IP Paris
Jean-Philippe Chancelier: IP Paris
Michel De Lara: IP Paris

Journal of Optimization Theory and Applications, 2025, vol. 207, issue 3, No 9, 33 pages

Abstract: Abstract The deployment of hydrogen infrastructures requires to reduce their costs. In this paper, we develop a multistage stochastic optimization model for the management, at least cost, of a hydrogen infrastructure which consists of an electrolyser, a compressor and a storage to serve a transportation demand. This infrastructure is powered by three different sources: on-site photovoltaic panels, renewable energy through a power purchase agreement and the power grid. We consider uncertainties affecting on-site photovoltaic production and hydrogen demand. Renewable energy sources are emphasized in the hydrogen production process to ensure eligibility for a subsidy, which is awarded if the proportion of nonrenewable electricity usage remains under a predetermined threshold. We formulate a multistage stochastic optimization problem, made of two coupled subproblems: an operational problem, management of the hydrogen equipment and the demand satisfaction; an electricity allocation problem, allocation of the electricity sources. Once decoupled with Lagrange duality, each subproblem is tackled by the dynamic programming algorithm, giving two sequences of Bellman functions, depending on a Lagrange multiplier which is updated. Finally, we obtain a state policy, based on a one-step minimization of an instantaneous cost plus a surrogate Bellman function, made of the sum of the operational and electricity allocation Bellman functions. The numerical results indicate that the algorithm provides relevant trajectories, and achieves a small duality gap, thus proving the effectiveness of this approach.

Keywords: Hydrogen infrastructure; Stochastic optimization; Lagrange decomposition (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-025-02795-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:207:y:2025:i:3:d:10.1007_s10957-025-02795-1

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-025-02795-1

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-10-11
Handle: RePEc:spr:joptap:v:207:y:2025:i:3:d:10.1007_s10957-025-02795-1