A Kriging-based approach for conjugating specific dynamic models into whole plant stationary simulations

Abstract

Steady-state simulators are usually applied for design, techno-economic analysis and optimization of industrial processes. However, sometimes dynamic systems are important parts of the process, which cannot be disregarded. Coupling a dynamic model within a full-plant for steady-state simulation is a challenging task, whatever might be the simulator concept, either sequential or equation-oriented. An alternative to solve this problem is the use of surrogate models to substitute specific dynamic models, by taking the variable time as an extra input of the meta-model. This methodology was applied in an equation-oriented simulator (EMSO) by the use of Kriging meta-models. A case study involving the production of bioethanol from sugarcane was used to demonstrate the capability of this approach. A Kriging meta-model used to substitute the kinetic model of an enzymatic hydrolysis reactor was conjugated into the global plant simulation and an optimization problem was successfully solved.