Multi-objective scheduling of a steelmaking plant integrated with renewable energy sources and energy storage systems: Balancing costs, emissions and make-span
Pengfei Su, Yue Zhou, Jianzhong Wu
Abstract
As an energy-intensive industry, the steel industry grapples with increasing energy costs and decarbonization pressures. Therefore, multi-objective optimization is widely applied in the production scheduling of the steelmaking plant. However, the optimal solution that prioritizes energy savings and emission reductions may lead to impractical or less economically efficient solutions, since the processing time requirement (PTR) of steel production orders in real-world production is neglected. This study fills the research gap by discussing the impact of PTR on the make-span of the steelmaking process and incorporating it into the optimization model. Considering the variability of PTR, the solving of the multi-objective scheduling problem is transformed into the selection from Pareto solutions with different make-spans. To better leverage the temporal flexibility of the steelmaking process, a what-if-analysis-based strategy coupled with the Normal Boundary Intersection method is proposed to generate a series of evenly distributed Pareto solutions. The energy storage system is integrated to improve the time granularity of the steelmaking plant's flexibility. Our case studies demonstrate that the electricity and emission costs are reduced by 68.5%, indirect emissions are reduced by 83.5%, while the on-site renewable energy self-consumption rate increases by 24.5%. The effectiveness of the proposed method implies that it is of great relevance to the development of a cleaner steel industry in the future.