Modeling of Reversible Solid Oxide Cells for Integrated Energy System Optimization Scheduling

Solid oxide fuel cell (SOFC) is recognized as pivotal technological component in the utilization of hydrogen energy, drawing extensive interest due to their high efficiency, low emissions, and cost-effectiveness. Reversible solid oxide cell (rSOC) is a promising technology that encompasses the functions of both SOFC and solid oxide electrolysis cell (SOEC), enabling bidirectional conversion between electricity and hydrogen within a single device. This study introduces an electrochemical-thermodynamic coupling (ETC) modeling approach suitable for the optimized scheduling of integrated energy system (IES). Initially, a model of the rSOC's electrochemical process was established. Subsequently, the thermodynamic process of the rSOC equipped with a waste heat recovery system is modeled to determine the temperature dynamics process of the rSOC. Besides, the degradation process of the rSOC is modeled. The ETC model of the rSOC is then segmented and linearized based on the simulated annealing algorithm, and the resulting linear model is integrated into the IES optimization scheduling framework. Finally, a case study based on an industrial park is conducted to simulate and validate the proposed method. The simulation utilizes Matlab and Cplex to solve the optimization problem, confirming the feasibility and superiority of the method in guiding the rSOC to participate in IES scheduling, reducing operational costs, and actively engaging in the hydrogen energy market.