Hybrid systems (HS) are highly attractive in power generation due to their potential for higher power outputs and efficiencies by integrating different technologies. Among solid oxide fuel cell (SOFC) plants, the SOFC-Micro-Gas Turbine (mGT) system is particularly innovative. In this setup, the SOFC replaces the mGT combustion chamber, with an afterburner completing fuel combustion before the expander. Various configurations and control systems have been explored over the years, and prototypes have demonstrated satisfactory efficiency. However, these systems have predominantly used NG and Biogas, which do not achieve zero carbon emissions. The growing global demand for carbon-free energy production is increasing, highlighting the importance of alternative fuels in the power generation sector: among them, thanks to its chemical and physical properties, ammonia is gaining more and more interest. This work investigates an innovative ammonia-to-power system based on an SOFC-mGT HS, focusing on thermodynamic parameters, system features, and technical and environmental challenges. A MATLAB/Simulink model, built on a validated HS model fueled by NG, was developed to analyze the new system configuration. This configuration replaces the SOFC prereformer with an ammonia cracker, allowing for the exploration of anode gas recirculation effects and optimal system design. Key operating parameters such as anodic recirculation factor, fuel utilization, performance, and gas turbine characteristics are discussed. Finally, a comparison is made between hybrid systems and mGTs powered by methane, biogas, and ammonia.

Power-to-Ammonia (P2A) is a promising technology that can provide a low-emission energy carrier for long-term storage. This study presents an optimization approach to a novel small-scale containerized P2A concept commissioned in 2024. A dynamic nonlinear optimization problem of the P2A concept is set up, employing the non-commercial MOSAIC^® software V3.0.1 in combination with the NEOS^® server. In total, seven optimization solvers, ANTIGONE^®, CONOPT^®, IPOPT^®, KNITRO^®, MINOS^®, PATHNLP^®, and SNOPT^®, are used. The first and main part of this work optimizes several disturbance scenarios of the concept and aims to determine the optimal reactor temperature profile to counter the disturbances. The optimization results suggest, for example, lowering the reactor temperature profile if the hydrogen and nitrogen inlet streams into the system decrease. The second part of this work presents a crude dynamic optimal scheduling model. This part aims to determine the amount of ammonia to be produced and sold given a randomized price of electricity for three consecutive points in time. The optimization results recommend decreasing production when the price of electricity is high and vice versa. However, the dynamic model must be improved to include fluctuations in the price of ammonia. Then, it can be used as a real-time optimization tool.