Multi-objective Optimization of the Energy System in an Iron and Steel Plant for Energy Saving and Low Emissions

The energy system in the iron and steel industry significantly contributes to the large energy consumption and emissions of CO2 and some air pollutants such as SO2 and NOx. Therefore, optimization of the energy system is highly desired in order to reduce energy consumption and those emissions. In this paper, a multi-objective multi-period planning model is developed for optimization of the energy system in an iron and steel plant, incorporating some important practical features such as fuel selection, gasholder level control, minimum heating requirements for single and mixed consuming users and ramp rate limits. The objective is to minimize the economic cost and environmental impact simultaneously. To solve the multi-objective optimization model, a new improved multi-objective particle swarm optimization algorithm is proposed, incorporating self-adaptive mutation and effective constraint handling strategies. The results demonstrate the superiority of the proposed approach to solve the multi-objective optimization problem.