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Multi-Objective Optimization of Cell Voltage Based on a Comprehensive Index Evaluation Model in the Aluminum Electrolysis Process

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Listed:
  • Chenhua Xu

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Wenjie Zhang

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Dan Liu

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Jian Cen

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China
    Guangzhou Intelligent Building Equipment Information Integration and Control Key Laboratory, Guangzhou 510665, China)

  • Jianbin Xiong

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Guojuan Luo

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

Abstract

In the abnormal situation of an aluminum electrolysis cell, the setting of cell voltage is mainly based on manual experience. To obtain a smaller cell voltage and optimize the operating parameters, a multi-objective optimization method for cell voltage based on a comprehensive index evaluation model is proposed. Firstly, a comprehensive judgment model of the cell state based on the energy balance, material balance, and stability of the aluminum electrolysis process is established. Secondly, a fuzzy neural network (FNN) based on the autoregressive moving average (ARMA) model is designed to establish the cell-state prediction model in order to finish the real-time monitoring of the process. Thirdly, the optimization goal of the process is summarized as having been met when the difference between the average cell voltage and the target value reaches the minimum, and the condition of the cell is excellent. And then, the optimization setting model of cell voltage is established under the constraints of the production and operation requirements. Finally, a multi-objective antlion optimization algorithm (MOALO) is used to solve the above model and find a group of optimized values of the electrolysis cell, which is used to realize the optimization control of the cell state. By using actual production data, the above method is validated to be effective. Moreover, optimized operating parameters are used to verify the prediction model of cell voltage, and the cell state is just excellent. The method is also applied to realize the optimization control of the process. It is of guiding significance for stabilizing the electrolytic aluminum production and achieving energy saving and consumption reduction.

Suggested Citation

  • Chenhua Xu & Wenjie Zhang & Dan Liu & Jian Cen & Jianbin Xiong & Guojuan Luo, 2024. "Multi-Objective Optimization of Cell Voltage Based on a Comprehensive Index Evaluation Model in the Aluminum Electrolysis Process," Mathematics, MDPI, vol. 12(8), pages 1-16, April.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:8:p:1174-:d:1375389
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    References listed on IDEAS

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    1. Koziel, Slawomir & Pietrenko-Dabrowska, Anna, 2022. "Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation," European Journal of Operational Research, Elsevier, vol. 299(1), pages 302-312.
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