Multi-objective optimization of gas-steam-power system for an integrated iron and steel mill considering carbon emission reduction and cost

Abstract

The gas-steam-power system (GSPS) optimization is a complicated optimization problem considering economic and environmental benefits. This paper presents a multiperiod mixed integer linear programming (MILP) model for the GSPS in iron and steel enterprises simultaneously optimizing total cost and carbon emission reduction. It was used to determine the optimal operating strategy for the GSPS under multiobjective conditions. The model considers the influence of a blast furnace with top-gas recycling (TGR-BF) technology on the by-product gas supply and steam and power cogeneration system (SPCS) operation. The results showed that after the optimization aiming at the minimum total cost (Scenario A) and the maximum carbon emission reduction (Scenario B), the system total cost was the lowest (7.78 billion CNY) when the top gas recovery rate was 4%, and the carbon emission reduction peaked at 465,296.76 tCO2 when the top gas recovery rate was 12%. After multiobjective optimization (Scenario C), it was found that the system achieved carbon reduction only when the total cost attained a certain value. A sensitivity analysis revealed that a reduction in the grid emission factor and an increase in the green power increased the carbon emission reduction. When the coal price increased to 1800 CNY/t or the power price decreased to 0.2 CNY/kWh, the optimal system operation strategy was consistent under different optimization objectives. These research results provide guidance for steel enterprises to reduce carbon emissions and total cost.