A recent study conducted in Dalian, China, presented an innovative approach to sustainable hydrogen production by integrating solar and wind energy for electrolyzers. The research focused on optimizing the hydrogen production system by proposing a novel source and load collaborative optimization strategy. This strategy aimed to tackle the challenges posed by the intermittent and variable nature of renewable energy sources. By utilizing the XGBoost algorithm for energy generation data analysis, the research team was able to predict optimal electrolyzer operation. The collaborative optimization strategy was designed to balance loads between electrolyzer arrays, minimize cold-start situations, prolong steady-state hydrogen production time, and reduce operational variations due to maintenance. The effectiveness of this strategy was validated through theoretical analyses and extensive simulation results, showing a significant reduction in the standard deviation of electrolyzer runtime. This improvement enhanced the overall system stability and contributed to reducing maintenance frequency. The conclusion drawn from the research emphasized the importance of integrating renewable energy sources for clean energy production. The proposed strategy not only enhanced hydrogen production efficiency but also provided a practical and effective solution for achieving green hydrogen production goals. The study was peer-reviewed and showcased the potential for advancing sustainable hydrogen production in China through innovative collaborative optimization strategies.