Nonlinear model predictive control of a modular hydrogen-ammonia and renewable energy generation system

This paper investigates the regulation of a modular renewable energy-integrated hydrogen-ammonia production system comprising a water electrolyzer connected to an ammonia synthesis reactor with a recycle loop. This chemical production module is driven by an integrated renewable solar and wind energy generation system. Oscillatory behavior is observed in the chemical process, characterized by significantly faster dynamic responses compared to the renewable energy module. Under typical weather conditions, the renewable energy supply cannot fully meet the chemical system’s energy demands. Employing nonlinear model predictive control, this work examines optimal management strategies to maintain desired chemical manufacturing system operations based on the instantaneous availability of renewable energy. Specifically, the study identifies the minimum supplemental energy required from the electrical grid to achieve a target chemical operation.