Modeling, parameter estimation and optimization of fluidized bed-based alternative ironmaking process for CO2 emission reduction

Abstract

This study presents the development of a comprehensive process model for simulating and optimizing the FINEX process consists of the multi-stage fluidized beds, the melter-gasifier unit, and a gas recycling system. The model is developed using Pyomo, a Python-based open-source software package that provides extensive capabilities for formulating, solving, and analyzing optimization models. It incorporates heat and mass balance equations and captures a wide range of chemical reactions, including the reduction of iron ore by hydrogen and carbon monoxide, the calcination of carbonate materials, the water–gas shift reaction, and coal gasification and combustion. Unknown parameters in the model, such as heat loss in each reactor, the extent of the calcination reaction, and the outlet gas temperature from the melter-gasifier, were estimated to calibrate the model. These parameters were estimated by solving an optimization problem that minimizes the gap between the model and real plant data. The optimized model was employed to investigate various scenarios for minimizing CO emissions in the FINEX process. This included assessing the impact of HBI charging rates, iron ore quality, and the integration of a CCUS unit. For each scenario, an optimization problem was formulated to minimize production costs across a range of CO tax levels. The optimal solutions revealed the relationships between process economics and CO emissions for each variable.