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.