A multi-dimensional control scheme for improving the performance of multi-electrolyzer green hydrogen production system

Global research on renewable energy (RE)-powered green hydrogen (H₂) production systems has increasingly focused on developing control schemes to improve the performance of multi-electrolyzer (EL) system configurations. Despite this progress, existing multi-EL control schemes focuses on optimizing trade-offs between competing multi-EL system performance metrics, such as maximizing RE utilization, minimizing EL start-stop cycles, and reducing EL operating hours, rather than addressing multiple interrelated and multidimensional performance metrics simultaneously. Furthermore, EL models employed for multi-EL system design do not sufficiently capture the coupled electrochemical and thermal dynamics of ELs. Critical parameters such as cold-start and hot-start behavior,efficiency variability, and overpotential losses (ohmic, activation, and diffusion overpotentials), are simplified or neglected. These assumptions can lead to suboptimal design and affect the accuracy of both the modeling framework and control scheme of the multi-EL system. In response to the identified research gaps, a first principles-based electrothermal PEM EL model was developed and integrated into a dynamic wind turbine (WT) system for the implementation of a multi-EL control scheme. Building on previous control schemes, CS-1 (equal power sharing), CS-2 (daisy chain), and CS-3 (rapid start-up with equal power allocation), a novel predictive adaptive load-balancing multi-EL control scheme (CS-4) is proposed to optimize multi-EL performance across several interrelated and multidimensional criteria. A comprehensive simulation-based comparison was conducted to evalaute the performance of all four control schemes. The proposed CS-4 control scheme demonstrated superior performance, improving efficiency by 9.66%, 5.99%, and 3.27% compared with CS-1, CS-2, and CS-3, respectively. It achieved the lowest load imbalance, with a standard deviation of 0.01956, compared with CS-2 and CS-3, and minimized start-stop cycles relative to CS-2. Additionally, compared with CS-1, CS-2, and CS-3, CS-4 increased WT power utilization by 14.1% (2943 MW), 12.97% (2723 MW), and 1.06% (250 MW), respectively. It also reduced unused WT power by 2945 MW (77.59%), 2723 MW (76.21%), and 250 MW (22.73%), while improving H₂ production by 0.559%, 0.505%, and 0.354%, respectively.