Multi-Objective Optimization of Steel Off-Gas in Cogeneration Using the ε-Constraint Method: A Combined Coke Oven and Converter Gas Case Study

Abstract

Increasingly demanding environmental regulations are forcing companies to reduce their impacts caused by their activity while defending the economic viability of their manufacturing processes, especially energy and carbon-intensive ones. Therefore, these challenges must be addressed by posing optimization problems that involve several objectives simultaneously, corresponding to different conditions, and often conflicting between. In this study, the residual gases of an integral steel factory were evaluated and modeled with the goal of developing an optimization problem considering two opposing objectives: CO2 emissions and profit. The problem was first approached in a mono-objective manner, optimizing profit through Mixed Integer Linear Programming (MILP), and then was extended to a bi-objective problem solved by means of the ε-constraint method, to find the Pareto front relating profit and CO2 emissions. The results show that multiobjective optimization is a very valuable resource for plant managers’ decision-making processes. The model makes it possible to identify inflection points from which the level of emissions would increase disproportionately. It gives priority to the consumption of less polluting fuels. The model also makes it possible to make the most of temporary buffers such as the gas holders, adapting to the hourly price of the electricity market. By applying this method, CO2 emissions decrease by more than 3%, and profit amounts up to 14.8% compared to a regular case under normal operating conditions. The sensitivity analysis of the CO2 price and CO2 constraints is also performed.