Causality Analysis of the Green Ammonia Synthesis Process Using the Convergent Cross Mapping Algorithm

Ammonia synthesis has been gradually altered from the
gray process
(using fossil fuels as hydrogen sources) to the green process (directly
or indirectly using water electrolytic cells as hydrogen sources powered
by renewable energy), with the motivation of sustainable development
and carbon neutrality. The fluctuating nature of renewable energy
and the location mismatch between power plants and the production
complex make gray ammonia production roadmaps likely to fail or embrace
the change. Establishing knowledge graphs in the form of causal relationship
network diagrams will help enterprise decision-makers and engineers
better understand the process and generate correct production operations
and scheduling. In this study, a chemical engineering-informed method
is introduced to generate causal networks of multiple load conditions
for green ammonia production. Expert knowledge of chemical engineering
is embedded in the determination of the existence and corresponding
time delay of the causal relationships of variable pairs. In an industrial
case study, the skeletal knowledge graphs and evolution of the control
mechanisms were identified in a comparison of the derived causal networks.
Extended applications are expected with further integration of controlling
theory and algorithms.