Modeling and Schedule Optimization of a Fuel Cell-Driven Multigeneration Process for Combined Production of Power, Blue Hydrogen, and Ammonia

In this work, a novel multigeneration process is modeled to produce compressed hydrogen, ammonia, and electricity. The hydrogen is recovered by a catalytic membrane reactor and all CO₂ is captured through a membrane while utilizing a high temperature solid oxide fuel cell for heat and electricity integration. A detailed chemical model for the proposed process is developed. In addition, the plant's operational scheduling optimization is conducted through two distinct methodologies: deterministic and stochastic rolling-horizon (RH) optimization. The stochastic RH approach addresses the price uncertainties involved in the optimization model. Extensive simulations are carried out to explore the merits of the proposed approaches. Moreover, sensitivity analyses are conducted to study the effect of price variations on the optimal plant responses. Simulation results show that hydrogen sales are usually favorable with current global prices, and utilizing the suggested stochastic RH approach results in an approximately 7% increase in achieved realized profit compared to the deterministic approach.