The primary objective of this work is to research and develop a dynamic model and an advanced control strategy for a reversible solid oxide fuel cell in a grid to ensure load tracking whilst maintaining fuel utilisation and temperature dynamics within a safe range. This report presents the successful development of the dynamic model and corresponding controller. To do so, modeling and control are discussed in two separate chapters where model requirements, specifications and conception are presented followed by the control techniques, control objectives and controller synthesis. A RSOFC model has successfully been developed and thoroughly validated against other literature. To do so, a set of fitting parameters has been distilled from literature to create a good overlap with other studies and are combined in a manner that they can be implemented in other work. Steady state dynamics and the transient dynamics have shown a good match to the available literature. Additionally, the model offers useful insights into RSOFC (transient) dynamics with relation to temperature effects, fuel composition and cell support structure, which have not been documented before. At last the RSOFC stack, together with the developed model has been built in a plug-and-play manner that it can be implemented and adjusted by others, to be used in combination with other models. For control an output-feedback adaptive nonlinear model predictive controller has been developed, which is an advanced version of the well established (non)linear model predictive controller. The development of the temperature controller is given wherein the structure of the MPC is presented together with its trajectory, adaptive constraints and tuning variables. After completing the development of the controller, the controller was simulated together with the dynamic model as part of a micro-grid. The simulations were split up into short and long term scenarios and showed satisfactory results as all the set control objectives were achieved.

The integration of variable renewable energy sources (RESs) in the electrical power grid leads to larger and faster variations in the power demanded from controllable power sources. This is a problem, because flexibility of (base load) power plants is limited. Solid oxide reversible cells(SORCs) can be used as load-shifting devices to reduce these power variations by converting electricity to hydrogen (solid oxide electrolysis cell (SOEC) mode) when power demand is low and converting hydrogen to electricity (solid oxide fuel cell (SOFC) mode) when power demand is high. However, the introduction of SORCs is challenging. It is a promising long-term energy storage technology, but it is in its development stage. Apart from prohibitive costs, challenges also lie within durability and efficiency under dynamic operation. Development of control strategies is essential for maintaining optimal operating conditions. Therefore, this study researches the ability of SORCs to operate in a mixed power grid by developing an SORC model and power disturbance rejection controller which ensures safe operating conditions. A dynamic 0D SORC model was developed. It describes a single cell at the center of a large stack of identical cells, which makes it representative for large-scale SORCs. The model is based on SOFC models and uses the current density to indicate the operating mode of the SORC. The benefit of this approach is that one continuous model describes both operating modes. Validation of the model is based on comparison of static cell voltage-current density curves from literature and from a small stack experiment. Open-loop analysis of the model showed that the system is stable and can be decoupled. It also showed that development of gain-scheduling controllers was necessary to handle the exothermic, hydrogen consuming SOFC mode and endothermic, hydrogen producing SOEC mode. This motivated the design of gain-scheduling H-infinity tuned proportional-integral (PI) controller, which were used to control the positive electrode, electrolyte, negative electrode (PEN) structure temperature and fuel channel composition by manipulating the air and fuel flow rate, respectively. Two methods were compared for specifying the performance of the controller. The first method was based on the desired closed-loop bandwidths and the second method was based on the bandwidth of the disturbance. The first method was superior to the second method, because the obtainable closed-loop bandwidths are faster than the bandwidth of the disturbance. This study shows that gain-scheduling PI controllers allow SORCs to be used for load shifting applications in a mixed power grid. Further research is needed to validate the dynamics of the model and to identify the influence of balance of plant (BOP) dynamics on controller performance.