Economically Optimal Scheduling and Commissioning Method of Power Generation and Consumption in Steel Industries Considering Time-of-Use Tariffs

The steel production process is characterized by multiple stages, multiple machines, and a mixture of discrete and continuous production. Optimizing scheduling and commissioning methods of power generation and consumption in this steel production process can reduce operation costs. This paper proposes a multi-objective scheduling and commissioning method optimization framework for the steel industry to minimize the electricity cost and carbon emissions in steel plants under time-of-use (TOU) tariffs. The proposed framework is formulated by using the mixed integer nonlinear programming (MINLP), which considers different production processes in steel plants, the carbon emission model, photovoltaic power generation, wind power generation, and TOU. The experimental results and comparative analysis prove that the proposed multi-objective optimal power generation and consumption economic model can save power costs and achieve a particular effect of load peaking.