Chemical Reactor Network modeling of ammonia–hydrogen combustion in a gas turbine: stochastic sensitivity analysis

To tackle climate change, we need to incorporate renewable energy sources on a large scale. One potential solution is the use of hydrogen, as an alternative energy vector that can be burnt in existing devices with little modification. Hydrogen can be produced from excess wind and solar power, ammonia, as a hydrogen carrier, is very appealing as it can be easily liquified and distributed through the existing infrastructure. This study aims to explore the feasibility of using ammonia–hydrogen mixtures in industrial settings. This exploration is made by modeling a gas turbine system through a network of chemical reactors (CRN) and it is aimed at improving our understanding of the energy conversion process involving hydrogen, ammonia, and their mixtures. In this work, we analyze the most significant parameters of the CRN model, leveraging stochastic techniques. Specifically, we study the effects of the model and operational parameters on NOx emissions. This could represent a valuable aid in the development of CRN models capable of predicting emissions from gas turbine systems, to understand the impact of various operating conditions, such as pressure, temperature, equivalence ratio, and mixture composition.