Multi-objective scheduling of a steelmaking plant integrated with renewable energy sources and energy storage systems: Balancing costs, emissions and make-span
Multi-objective scheduling of a steelmaking plant integrated with renewable energy sources and energy storage systems: Balancing costs, emissions and make-span
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DOI：
10.1016/j.jclepro.2023.139350
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发表时间：
2023-10
影响因子：
11.1
通讯作者：
Pengfei Su;Yue Zhou;Jianzhong Wu
中科院分区：
文献类型：
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作者：
Pengfei Su;Yue Zhou;Jianzhong Wu
作为能源密集型行业，钢铁行业面临着不断增加的能源成本和脱碳压力。因此，多目标优化在炼钢厂生产调度中得到广泛应用。然而，优先考虑节能减排的最优解决方案可能会导致不切实际或经济效率较低的解决方案，因为忽略了实际生产中钢铁生产订单的处理时间要求（PTR）。本研究通过讨论PTR对炼钢过程的生产跨度的影响并将其纳入优化模型来填补研究空白。考虑到PTR的可变性，多目标调度问题的求解转化为不同制造周期Pareto解的选择。为了更好地利用炼钢过程的时间灵活性，提出了一种基于假设分析的策略与正态边界相交方法相结合，以生成一系列均匀分布的帕累托解。集成储能系统，提高炼钢厂灵活性的时间粒度。我们的案例研究表明，电力和排放成本降低了68.5%，间接排放减少了83.5%，现场可再生能源自耗率提高了12.1%。该方法的有效性意味着它对未来清洁钢铁行业的发展具有重要意义。
As an energy-intensive industry, the steel industry grapples with increasing energy costs and decarbonisation pressures. Therefore, multi-objective optimisation is widely applied in the production scheduling of the steelmaking plant. However, the optimal solution prioritising 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 optimisation 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%, and the on-site renewable energy self-consumption rate increases by 12.1%. The effectiveness of the proposed method implies that it is of great relevance to the development of a cleaner steel industry in the future.