Multi-cycle steel energy planning optimization based on improved NSGA-II algorithm

With a low energy efficiency, the iron and steel industry need a lot of materials and energy in the production process, which causes a lot of waste. In order to achieve sustainable steelmaking, a reasonable energy plan is made for the entire steel process to meet the needs of energy saving and consumption reduction. According to the characteristics of energy flow network in iron and steel industry, a mixed integer nonlinear programming (MINLP) model is established. Considering the time of use electricity price and the energy medium conversion balance, the objective functions are set up to minimize economic operation costs and net energy consumption. In addition, the improved non-dominated sorting genetic algorithm-II (NSGA-II) is designed to improve the quality of the solution. The case study shows that the energy plan optimization achieves the energy saving and reduction of economic costs of the enterprise.