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Aluminum electrolysis production optimization method based on SPEA2 algorithm

An optimization method and technology of aluminum electrolysis, applied in computing, electrical digital data processing, special data processing applications, etc., can solve the problems of environmental pollution, low efficiency, high energy consumption, etc., to reduce energy consumption per ton of aluminum and reduce emissions , the effect of improving the current efficiency

Inactive Publication Date: 2016-02-03
CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0003] This application provides an optimization method for aluminum electrolysis production based on the SPEA2 algorithm to solve the technical problems of huge energy consumption, low efficiency and serious environmental pollution caused by the inability to obtain optimal process parameters in the aluminum electrolysis production process in the prior art

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  • Aluminum electrolysis production optimization method based on SPEA2 algorithm
  • Aluminum electrolysis production optimization method based on SPEA2 algorithm
  • Aluminum electrolysis production optimization method based on SPEA2 algorithm

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Embodiment

[0057] Such as figure 1 As shown, an aluminum electrolysis production optimization method based on the SPEA2 algorithm includes the following steps:

[0058] S1: Count the original variables that have an impact on current efficiency, energy consumption per ton of aluminum and perfluoride emissions in the aluminum electrolysis production process, and determine the parameters that have a large impact on current efficiency, energy consumption per ton of aluminum and perfluoride emissions as Decision variable X;

[0059] Through the statistics of the measured parameters in the actual industrial production process, the current efficiency y 1 And greenhouse gas emissions 2 The most influential variable is: series current x 1 , Cutting times x 2 , Numerator ratio x 3 , Aluminum output x 4 , Aluminum level x 5 , Electrolyte level x 6 , Bath temperature x 7 , Cell voltage x 8 There are 8 variables in total.

[0060] S2: Collect the samples of decision variable X and its corresponding current...

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Abstract

The invention provides an aluminum electrolysis production optimization method based on an SPEA2 algorithm. The optimization method comprises the steps that modeling is conducted on the aluminum electrolysis production process by means of a BP neural network firstly; then optimizing is conducted by means of a production process model based on the SPEA2 algorithm to obtain a set of optimal solutions of all decision variables and current efficiency, ton aluminum energy consumption and perfluoro-compound discharge amount which correspond to the optimal solutions. By means of the aluminum electrolysis production optimization method based on the SPEA2 algorithm, the optimal values of technological parameters in the aluminum electrolysis production process are determined, the current efficiency is effectively improved, the ton aluminum energy consumption is reduced, greenhouse gas discharge amount is reduced, and the purposes of energy conservation and emission reduction are really achieved.

Description

Technical field [0001] The invention relates to the field of optimal control, in particular to an aluminum electrolysis production optimization method based on the SPEA2 algorithm. Background technique [0002] The environmentally friendly aluminum electrolysis production process has long been a challenging problem. In the electrolytic aluminum industry, the ultimate goal is to improve current efficiency, reduce energy consumption per ton of aluminum, and reduce perfluoride emissions on the basis of the smooth operation of electrolytic cells. However, this goal is very difficult to achieve because of aluminum electrolysis. There are many tank parameters, and the parameters show nonlinearity and strong coupling, which brings great difficulty to the modeling of aluminum electrolysis production process. BP neural network has strong non-linear mapping ability, suitable for solving the problem of nonlinear system modeling, and provides a new idea for modeling aluminum electrolysis pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 易军黄迪李太福何海波周伟张元涛陈实刘兴华
Owner CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
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