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Communication Dans Un Congrès Année : 2023

Unraveling the Competition: Power-to-Gas vs. Energy Storage, Insights from a Stochastic Dynamic Programming Approach

Camille Megy

Résumé

This study investigates the interplay between Power-to-Gas (PtG) and energy storage within an integrated electricity and hydrogen system. A Multistage Stochastic Dynamic Programming (MSDP) model, solved using the Stochastic Dual Dynamic Programming (SDDP) algorithm, captures the unpredictability of Variable Renewable Energy (VRE) sources in a German energy system forecast for 2035. Across four scenarios of installed PtG capacities, we scrutinize PtG's contributions to the energy system and how its deployment affects the operation and profitability of energy storage technologies. Our findings reveal PtG's efficacy in lowering electricity curtailment without markedly influencing electricity storage operations. PtG fosters low-carbon hydrogen production, diminishing reliance on hydrogen imports and fortifying hydrogen storage viability. However, this study underscores a critical aspect: the profitability of PtG experiences a significant downturn with expanding capacity, to the extent that it could threaten its overall viability. Public support may be imperative to ensure PtG's widespread adoption, addressing the economic challenges associated with its scalability.
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Dates et versions

hal-04297212 , version 1 (21-11-2023)

Identifiants

  • HAL Id : hal-04297212 , version 1

Citer

Ange Blanchard, Camille Megy. Unraveling the Competition: Power-to-Gas vs. Energy Storage, Insights from a Stochastic Dynamic Programming Approach. AFSE, Science Po Paris, Jun 2023, Paris, France. ⟨hal-04297212⟩
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