Different from low-temperature electrolysis systems, the large power consumption for the balance of plant (BOP) of the reversible solid oxide cell (RSOC) system for a high-temperature operating condition needs to be considered in the determination of the capacity configuration of the hybrid renewable energy (HRE) system. To address this issue, a power-based model of the RSOC system is developed and the corresponding capacity configuration strategy especially for the HRE system is also proposed in this paper. An optimization program of a hybrid energy system model composed of the wind turbines (WT), photovoltaic panels (PV), reversible solid oxide cell (RSOC) system, hydrogen storage tank (HST), and battery are presented to urge the minimization of the total system cost, power redundancy, and power shortage. Particle swarm optimization (PSO) algorithm is utilized to determine the optimum size and operational energy management within the system. The results show that after the regulation of the energy storage system, the power redundancy and shortage of the hybrid energy system are greatly reduced with the decreases by 85.08% and 64.42%, respectively. Moreover, the power mismatch is still significantly affected by seasons. It is also found that the energy storage efficiency of the RSOC system is within 20% due to the fact that part of the electric energy is consumed by the BOP to maintain the operation of the RSOC system. Thus, more improvements should focus on simplifying the BOP system of the RSOC system and reducing the excess power consumption in the future.

Solid oxide electrolysis cells (SOECs) have great application prospects because of their excellent performance, but the long-term applications of the stacks are restricted by the structural degradation under the high-temperature conditions. Therefore, an SOEC degradation model is developed and embedded in a process model of the high-temperature steam electrolysis (HTSE) system to investigate the influence of the stack degradation at the system level. The sensitivity analysis and optimization were carried out to study the influence factors of the stack degradation and system hydrogen production efficiency and search for the optimal operating conditions to improve the hydrogen production efficiency and mitigate the stack degradation. The analysis results show that the high temperature and large current density can accelerate the stack degradation but improve the hydrogen production efficiency, while the high temperature gradually becomes unfavorable in the late stage. The low air-to-fuel feed ratio is beneficial to both the degradation rate and hydrogen production efficiency. The results show that the optimization method can improve the hydrogen production efficiency and inhibit the stack degradation effectively. Moreover, part of the hydrogen production efficiency has to be sacrificed in order to obtain a lower stack degradation rate.