Nodal Marginal Price Decomposition Mechanism for the Hydrogen Energy Market Considering Hydrogen Transportation Characteristics

With the growing significance of hydrogen in the global energy transition, research on its pricing mechanisms has become increasingly crucial. Focusing on hydrogen markets predominantly supplied by electrolytic production, this study proposes a nodal marginal hydrogen price decomposition algorithm that explicitly incorporates the time-delay dynamics inherent in hydrogen transmission. A four-dimensional price formation framework is established, comprising the energy component, network loss component, congestion component, and time-delay component. To address the nonconvex optimization challenges arising in the market-clearing model, an improved second-order cone programming method is introduced. This method effectively reduces computational complexity through the reconstruction of time-coupled constraints and reformulation of the Weymouth equation. On this basis, the analytical expression of the nodal marginal hydrogen price is rigorously derived, elucidating how transmission dynamics influence each price component. Empirical studies using a modified Belgian 20-node system demonstrate that the proposed pricing mechanism dynamically adapts to load variations, with hydrogen prices exhibiting a strong correlation with electricity cost fluctuations. The results validate the efficacy and superiority of the proposed approach in hydrogen energy market applications. This study provides a theoretical foundation for designing efficient and transparent pricing mechanisms in emerging hydrogen markets.

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Publication Details

Journal
Energies
Published
2025-10-29
DOI
https://doi.org/10.3390/en18215681
Primary Topic
Electric Power System Optimization
Type
article
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article

Nodal Marginal Price Decomposition Mechanism for the Hydrogen Energy Market Considering Hydrogen Transportation Characteristics

Wei Yang, Shouheng Li, Kangkang Wang, Anan Zhang
Energies
Electric Power System Optimization
article

Nodal Marginal Price Decomposition Mechanism for the Hydrogen Energy Market Considering Hydrogen Transportation Characteristics

Wei Yang, Shouheng Li, Kangkang Wang, Anan Zhang
article en

Abstract

With the growing significance of hydrogen in the global energy transition, research on its pricing mechanisms has become increasingly crucial. Focusing on hydrogen markets predominantly supplied by electrolytic production, this study proposes a nodal marginal hydrogen price decomposition algorithm that explicitly incorporates the time-delay dynamics inherent in hydrogen transmission. A four-dimensional price formation framework is established, comprising the energy component, network loss component, congestion component, and time-delay component. To address the nonconvex optimization challenges arising in the market-clearing model, an improved second-order cone programming method is introduced. This method effectively reduces computational complexity through the reconstruction of time-coupled constraints and reformulation of the Weymouth equation. On this basis, the analytical expression of the nodal marginal hydrogen price is rigorously derived, elucidating how transmission dynamics influence each price component. Empirical studies using a modified Belgian 20-node system demonstrate that the proposed pricing mechanism dynamically adapts to load variations, with hydrogen prices exhibiting a strong correlation with electricity cost fluctuations. The results validate the efficacy and superiority of the proposed approach in hydrogen energy market applications. This study provides a theoretical foundation for designing efficient and transparent pricing mechanisms in emerging hydrogen markets.

EnergiesVol. 18(21)
Electric Power Research Institute (US), Southwest Petroleum University (CN), State Grid Corporation of China (China) (CN), Economic Research Institute (BG)
Openalex Percentile: Top 69%
Electric Power System Optimization
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Nodal Marginal Price Decomposition Mechanism for the Hydrogen Energy Market Considering Hydrogen Transportation Characteristics — Wei Yang, Shouheng Li, et al. · Energies (2025) | TGRS Research Map | TGRS