Due to the random fluctuations in power experienced by high-temperature green electric hydrogen production systems, further deterioration of spatial distribution characteristics such as temperature, voltage/current, and material concentration inside the solid oxide electrolysis cell (SOEC) stack may occur. This has a negative impact on the system's flexibility and the corresponding control capabilities. In this paper, based on the SOEC electrolytic cell model, a comprehensive optimization method using an adaptive incremental Kriging surrogate model is proposed. The reliability of this method is verified by accurately analyzing the dynamic performance of the SOEC and the spatial characteristics of various physical quantities. Additionally, a thermal dynamic analysis is performed on the SOEC, and an adaptive time-varying LPV-MPC optimization control method is established to ensure the temperature stability of the electrolysis cell stack, aiming to maintain a stable, efficient, and sustainable SOEC operation. The simulation analysis of SOEC hydrogen production adopting a variable load operation has demonstrated the advantages of this method over conventional PID control in stabilizing the temperature of the stack. It allows for a rapid adjustment in the electrolysis voltage and current and improves electrolysis efficiency. The results highlighted that the increase in the electrolysis load increases the current density, while the water vapor, electrolysis voltage, and H2 flow rate significantly decrease. Finally, the SOEC electrolytic hydrogen production module is introduced for optimization scheduling of energy consumption in Xinjiang, China. The findings not only confirmed that the SOEC can transition to the current load operating point at each scheduling period but also demonstrated higher effectiveness in stabilizing the stack temperature and improving electrolysis efficiency.