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With the development of renewable energy, the combination of industrial production and renewable energy has become the focus of research in recent years, and demand response is widely used in the field of electric power. So it is of great significance to use demand response for industrial processes that use renewable energy for production. However, there are few academic studies in this area, especially those involving the optimization of the demand response for the dispatching of electricity used for specific industrial production. Based on the above, the alumina production with renewable energy as the main energy supply is taken as the research object, and the real-time regulation of green power for plant electricity consumption is taken as the demand response object, and a multi-objective demand response model of electricity consumption for alumina production is established with the goal of satisfying the system economy and guaranteeing the yield on the basis of guaranteeing that the rate of wind and solar abandonment is minimized, and a genetic algorithm and a NBI (Normal- Boundary Intersection) algorithms were used to solve the model. Considering power cost, the alumina power cost per unit and abandonment rate under 6 scenarios are compared. The results show that alumina production with optimal scheduling using the NBI algorithm is able to reduce the cost of electricity per ton of alumina by 35%–75%, and reduce the rate of wind and solar abandonment by up to 9%.

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Multi-Objective Optimal Scheduling Study of Green Power and Low-Carbon Aluminum-Based Synergies Under the “Dual-Carbon” Objective

  • 会议论文

  • 发表日期：

    2025年

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  • Baoyong Liu,
  • Yitong Lin,
  • Liang Tang,
  • Haohan Tang,
  • Shenglong Fan

摘要

With the development of renewable energy, the combination of industrial production and renewable energy has become the focus of research in recent years, and demand response is widely used in the field of electric power. So it is of great significance to use demand response for industrial processes that use renewable energy for production. However, there are few academic studies in this area, especially those involving the optimization of the demand response for the dispatching of electricity used for specific industrial production. Based on the above, the alumina production with renewable energy as the main energy supply is taken as the research object, and the real-time regulation of green power for plant electricity consumption is taken as the demand response object, and a multi-objective demand response model of electricity consumption for alumina production is established with the goal of satisfying the system economy and guaranteeing the yield on the basis of guaranteeing that the rate of wind and solar abandonment is minimized, and a genetic algorithm and a NBI (Normal- Boundary Intersection) algorithms were used to solve the model. Considering power cost, the alumina power cost per unit and abandonment rate under 6 scenarios are compared. The results show that alumina production with optimal scheduling using the NBI algorithm is able to reduce the cost of electricity per ton of alumina by 35%–75%, and reduce the rate of wind and solar abandonment by up to 9%.