Multistage stochastic optimization of a mono-site hydrogen infrastructure by decomposition techniques
Abstract
The development of hydrogen infrastructures requires to reduce their costs.
In this paper, we develop a multistage stochastic optimization model for the
management 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 (PV),
renewable energy through a power purchase agreement (PPA) 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 stays under a predetermined threshold. We
solve the multistage stochastic optimization problem using a decomposition
method based on Lagrange duality. The numerical results indicate that the
solution to this problem, formulated as a policy, achieves a small duality gap,
thus proving the effectiveness of this approach.
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