Dynamic system-level rSOC model for solar-responsive and grid-adaptive optimal operation

This work presents a dynamic model of a reversible solid oxide cell (rSOC) plant operating under variable solar generation and electricity demand to enable optimal operation analysis. The model integrates a one-dimensional representation of the rSOC stack, capturing solid and gas temperatures, mass flow rates, and electrochemical performance, with zero-dimensional models of key heat-transfer units in the balance-of-plant (BoP). The innovation of this approach lies in the fully coupled framework, which combines the non-linear multi-physics of the stack with advanced physical representations of the BoP, including phase-change dynamics in the evaporator and regime-dependent heat transfer. A 24-hour simulation was performed to evaluate mode switching between solid oxide fuel cell (SOFC) and solid oxide electrolysis cell (SOEC) while tracking stack thermal stress and power. A multi-objective optimisation based on Latin Hypercube Sampling identified operating conditions that maximised electrical efficiency and reduced maximum temperature gradients in the stack. Dynamic plant analysis of a 10% step change in applied current for SOFC mode revealed that the BoP thermal inertia induces slower, more complex responses of average temperature and voltage, both displaying oscillatory behaviour. Characteristic corrected responses were fitted using parallel—first order lags and second order—transfer functions, yielding slow time constants of approximately τ ~ 219 s for voltage and τ ~ 273 s for average stack temperature. The similar time scales indicate the strong coupling introduced by BoP dynamics, with temperature only 1.25 times slower than voltage, contrasting with the isolated stack, where temperature responded 2.8 times slower. These findings provide a realistic framework for evaluating rSOC plants in renewable-integrated systems and support the development of advanced control strategies to ensure stable operation under intermittent energy inputs.