Grid-integrated electrolyzer systems are increasingly deployed for green hydrogen production, which is a promising pathway for energy decarbonization. However, their operation is challenged by insufficiently understood dynamic interactions among the grid-side rectifier, the buck converter, their control loops, and the electrolyzer stack. To address this issue, this paper develops a holistic analytical framework for such systems. A unified model is derived by integrating the rectifier, the buck converter, their control loops, and the electrolyzer stack. Based on this model, eigenvalue, participation-factor, and frequency-response analyses are conducted to systematically quantify stability characteristics, internal dynamic couplings, and parameter sensitivities. For a 2 MW electrolyzer case, the results reveal that excessive rectifier or buck-control bandwidths can independently trigger distinct oscillatory instabilities. On this basis, engineering-oriented controller-tuning guidelines are established, recommending about 10–50 Hz for the phase-locked loop, below about 60 Hz for the DC-link voltage controller, and about 20–150 Hz for the buck power controller. The analysis further shows that properly designed buck bandwidth renders the system-level power response weakly sensitive to slow electrolyzer dynamics dominated by double-layer capacitance, thereby mitigating uncertainty in this capacitance and clarifying the applicability of reduced-order electrolyzer models. These findings are corroborated by PSCAD/EMTDC time-domain simulations, verifying the effectiveness of the proposed analytical model. Additional verifications under frequency and voltage disturbances further confirm the model’s predictive capability, with maximum relative errors of 0.264%–1.486% and 0.153%–5.922%, respectively. Overall, this work offers an efficient analytical tool for stability-oriented control design, model-fidelity selection, and dynamic interaction analysis of grid-integrated electrolyzer systems.

Converter-interfaced renewable generation predominates in the development of new power system architectures, particularly in offshore systems. The increase of such multi-converter systems leads to the introduction of a new interaction among the different elements of the system and, therefore, new dynamic phenomena. Such phenomenon is subsynchronous and supersynchronous oscillations (SSO) which result, among other causes, from the interaction of converters with weak networks, such as offshore power systems. Various factors, including the challenge of obtaining analytical models from converter-based generation manufacturers and analysing system measurements during planning and operations, necessitate effective measurement-based methods for the swift and numerically trustworthy identification of various characteristics of SSO. Therefore, this paper analyses the advantages and disadvantages of the Dynamic Mode Decomposition method for identifying SSO. The theoretical background of the technique and the application algorithm are presented. The method is first applied to several synthetic signals exhibiting subsynchronous and supersynchronous modes under various conditions, including noise and different time windows. Then, a converted-based resource connected to an infinite bus is presented, and the method is applied to a group of recorded signals from this system under an external perturbation. This method is proposed as an alternative for analysing SSO in converted-based systems due to its ability to assess non-linear systems and its robustness against noise.