Control-oriented dynamic modeling and thermodynamic analysis of solid oxide electrolysis system

Abstract

Solid oxide electrolysis cell (SOEC) is a potential technology for increasing renewable energy penetration by turning excess power into hydrogen-based chemical energy, due to its high efficiency. In light of the intermittency of renewable energy, SOEC has to operate in a dynamic-changing environment. Therefore, dynamic modeling and thermodynamic analysis of solid oxide electrolysis systems are crucial for control design and efficient operation. In order to address various voltage losses, this paper develops a dynamic model of the solid oxide electrolysis system, in which the stack voltage is derived based on the electrochemical mechanism. The stack temperature is described by considering the dynamics of convective and radiative heat transfer between the layers. Dynamics of balance of plant (BOP) are modeled based on the mass and energy conservation laws. The model accuracy is verified by the polarization curve under different temperatures. The effects of temperature and current density on the electrolytic voltage are discussed. Three different operation modes (endothermic, thermoneutral and exothermic) are discussed in terms of different current density regions, where the balance between the electrochemical loss and reaction heat consumption varies. Steady-state energy and exergy flow diagrams are used to compare the energy consumption of different components in terms of different inlet temperatures, aiming to determine the optimal conditions with maximum system efficiency. The electrolyzer is revealed as the component with the highest energy consumption and exergy destruction. Dynamic simulation of the stack temperature is carried out in response to various control inputs and disturbances. Dynamic simulation exhibits the response rapidity of variables, strong couplings and different variation trends (monotone, overshoot or initial inverse response), due to the different time scales of electrochemical reaction, gas flow and heat transfer. This study lays a solid foundation for system optimization and dynamic control design.