Robust control of renewable-hydrogen electrolyzer-buck converter systems using modified double integral sliding mode controller for grid ancillary services

Accurate modeling of electrolyzer systems is essential to capture their intrinsic electrochemical characteristics, while robust control is critical to mitigate degradation and enhance energy efficiency. Together, these aspects enable electrolyzers to serve effectively as electrochemical power sources and renewable energy storage enablers. However, the existing literature often overlooks detailed modeling, limiting the robustness of advanced control strategies. Moreover, the application of non-linear control in assisting electrolyzers to provide grid-frequency ancillary services remains underexplored. To address these gaps, this paper proposes a novel state-space averaged (SSA) model of a proton exchange membrane (PEM) electrolyzer-buck converter system, incorporating the detailed dynamics of the electrolyzer’s electrical equivalent circuit. Based on this model, a modified sliding surface-based double integral sliding mode (DSM) control is proposed and systematically designed, ensuring finite-time convergence using Lyapunov criterion. The proposed control’s performance is rigorously validated against single integral sliding mode (SSM) control and proportional-integral (PI) control to regulate the electrolyzer’s input voltage in both steady-state and unpredictable conditions, as well as facilitating its dynamic power response during grid frequency disruptions. Furthermore, its efficacy in improving grid frequency resilience is demonstrated in a modified IEEE 13-bus distribution feeder system. The proposed DSM control exhibits superior performance in minimizing steady-state error, enhancing dynamic response, and augmenting robustness against varying operating and grid conditions. The results highlight its potential for both effective local management of the electrolyzer system and enhancing grid frequency stability, making it suitable for renewable integrated power systems. • Novel state-space model better captures PEM electrolyzer–converter dynamics. • Proposed modified DSM controller ensures robust voltage regulation. • DSM reduces degradation and enhances energy efficiency of electrolyzer system. • DSM control outperforms PI and SSM with faster, more stable power response. • DSM enhances system-level electrolyzer integration and grid frequency support.