Modeling megawatt-scale hydrogen electrolysis plants with frequency support capability

With the growing integration of intermittent renewable energy, hydrogen electrolyzers (HEs) are emerging as vital power-to-gas assets. However, utilizing these systems for ancillary services like Frequency Sensitive Mode (FSM) and Virtual Synchronous Mechanism (VSM) impacts their internal dynamics, a topic that remains underexplored. To analyze these interactions, this study develops a hybrid dynamical modeling framework and assesses its performance under FSM/VSM operation through a MW-scale case study. This framework integrates lumped HE electrolyzer models with first-order dynamic approximations of the peripheral balance-of-plant (BoP) components. The HE model accurately emulates the 17.5 MW Siemens Silyzer 300, successfully reproducing manufacturer polarization curves and transient responses. Findings highlight that the Silyzer 300 cells operate within a current density range of 0.16 to 2.5 A/cm2, yielding stack efficiencies between 76.32% and 99.71% and cell voltages from 1.49 to 1.94 V. While maximum efficiency occurs at 80 C and 1 bar, the electrolyzer demonstrates similar efficiencies at current densities below 0.5 A/cm2, regardless of the temperature. To evaluate its performance within a 1000 MW wind farm scenario, the HE plant was scaled to a 507 MW capacity, comprising 29 Silyzer 300 modules. The study further quantifies the inherent trade-off between grid stabilization and production consistency. Although FSM and VSM activation effectively mitigate frequency and voltage deviations, it induces fluctuations in hydrogen output and thermal stress, particularly when stack efficiencies drop below 85%. Furthermore, the sensitivity analysis highlights the critical role of BoP dynamics in determining the suitability of HEs for FSM applications. While this suitability depends on installation’s intrinsic characteristics, results show that slow HE BoP dynamics offer limited frequency support during fast frequency transients. Ultimately, the proposed hybrid framework serves as a robust approach, offering a predictive tool for operators to optimize large-scale hydrogen production while maintaining grid resilience.