Dynamic modeling and control strategy optimization of photovoltaic-electrolyzer system via equivalent dynamic impedance

Abstract

To address the dynamic mismatch between photovoltaic (PV) generation and alkaline water electrolysis in green hydrogen production systems, this study proposes an integrated dynamic modeling framework incorporating equivalent dynamic impedance. A nonlinear model comprising a PV array, DC–DC converter, and alkaline electrolyzer is established, elucidating how impedance matching governs electrolyzer performance under solar irradiance fluctuations. Real-time current–voltage feedback enables accurate characterization of the dynamic response within the 0.1–0.4 A/cm² range. Genetic algorithm optimization yields an optimal configuration: proportional gain = 14.93; integral gain = 1.97; 29.77 wt% KOH concentration; and 368.14 K operating temperature, achieving 82.67 % system efficiency. The equivalent dynamic impedance model, combined with an improved adaptive step-size P&O algorithm, reduces dynamic response time to below 10 ms and energy efficiency fluctuation error to 1.1 % (versus 3.2 % under static impedance). Simulations demonstrate superior hydrogen production rate tracking under cloudy conditions compared to conventional methods. This work provides a novel theoretical foundation for real-time control of PV-electrolyzer systems, enhancing stability for practical deployment.