A method of optimizing cell voltage based on STA-LSSVM model

C Xu, Z Tu, W Zhang, J Cen, J Xiong, N Wang - Mathematics, 2022 - mdpi.com
It is challenging to control and optimize the aluminum electrolysis process due to its non-
linearity and high energy consumption. Reducing the cell voltage is crucial for energy …

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

C Xu, W Zhang, D Liu, J Cen, J Xiong, G Luo - Mathematics, 2024 - mdpi.com
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 …

Intelligent optimization of cell voltage for energy saving in process of electrolytic aluminum

C Xu, L Wang, X Lin, Z Li, X Yu - Journal of Advanced Computational …, 2016 - jstage.jst.go.jp
Based on the characteristic of cell voltage fluctuations in the process of electrolytic
aluminum, a new method based on neural-network-genetic-algorithm (NNGA) for the …

A Novel Method of Local Anode Effect Prediction for Large Aluminum Reduction Cell

J Cui, Z Li, X Li, B Liu, Q Li, Q Yan, R Huang, H Lu… - Applied Sciences, 2022 - mdpi.com
Featured Application Local anode effects occur more frequently in large-scale aluminum
electrolysis cell systems. But the existing equipment can only detect global anode effects …

Time series clustering method with cluster validation to identify unknown local cell conditions in the aluminum reduction cell

Z Huang, C Yang, X Chen, X Zhou, W Gui - Computers & Industrial …, 2022 - Elsevier
It is important to identify local cell conditions in the aluminum reduction cell for cell control.
However, in the actual aluminum electrolysis process, local cell conditions are unknown …

Anode effect prediction based on collaborative two-dimensional forecast model in aluminum electrolysis production.

Z Chen, Y Li, X Chen, C Yang… - Journal of Industrial & …, 2019 - search.ebscohost.com
In this study, a new prediction algorithm is proposed, based on the collaborative two-
dimensional forecast model (CTFM) that combines the traditional method and similarity …

An advanced nonlinear control approach for aluminum reduction process

J Shi, Y Yao, J Bao, M Skyllas-Kazacos, BJ Welch… - Light Metals 2020, 2020 - Springer
With the increase in amperage and associated reduction of electrolyte volume to anode
surface ratio, the existing cell control method is facing more challenges due to greater …

Development of low-voltage energy-saving aluminum reduction technology

L Jie, L Xiao-Jun, Z Hong-Liang, L Ye-Xiang - Light metals 2013, 2016 - Springer
In this study, the representative low-voltage energy-saving techniques for aluminum
reduction in recent years in China is reviewed, and two low-voltage energy-saving …

A modified neighborhood mutual information and light gradient boosting machine-based long-term prediction approach for anode effect

H Pan, L Kong, X Chen, K Zhou, J Liu… - … Science and Technology, 2019 - iopscience.iop.org
The anode effect (AE) often occurs in the aluminum electrolysis process, which seriously
affects production efficiency and causes large energy consumption. Therefore, predicting AE …

[HTML][HTML] A novel hybrid analysis and modeling approach applied to aluminum electrolysis process

ETB Lundby, A Rasheed, JT Gravdahl… - Journal of Process …, 2021 - Elsevier
Aluminum electrolysis cells are characterized by harsh environments where several
measurements have to be done manually. Due to the operational costs related to manual …