Aluminum electrolysis preference multi-target optimization algorithm based on angle dominance relation

A technology of multi-objective optimization and dominance relationship, applied in the field of aluminum electrolysis preference multi-objective optimization algorithm, can solve the problems of low efficiency, environmental pollution, high energy consumption, etc., to reduce emissions, reduce energy consumption per ton of aluminum, and improve current efficiency Effect
CN109085752AActive Publication Date: 2018-12-25CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
7 Cites 4 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
Publication Date
2018-12-25

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses an aluminum electrolysis preference multi-target optimization algorithm based on the angle dominance relation. Firstly, modeling is conducted on the aluminum electrolysis production process through a recurrent neural network; then, an expected target value is set by a decision maker; and then, a production process model is optimized through a preference multi-target quantumindividual group algorithm, and a set of optimal solutions, meeting expectation of the decision maker best, of all decision variables and the current efficiency, the bath voltage, the perfluorocompound emission amount and per-ton aluminum energy consumption which correspond to the optimal solutions are obtained. Through variation, crossing and selecting operation in a differential evolution algorithm, the decision variables are subjected to preference optimizing, thus the optimal value of technological parameters in the aluminum electrolysis production process is determined, the current efficiency can be effectively improved, the bath voltage is lowered, the greenhouse gas emission amount and per-ton aluminum energy consumption are reduced, and the purposes of energy conservation and emission reduction are achieved while preference of the decision maker is met.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention belongs to the field of optimal control, in particular to a multi-objective optimization algorithm for aluminum electrolysis preference based on angle dominance relationship. Background technique

[0002] The environmentally friendly production process of aluminum electrolysis has long been valued, but it is very challenging. In the electrolytic aluminum industry, the ultimate goal is to improve current efficiency, reduce cell voltage, reduce perfluorinated compounds, and reduce emissions per ton of aluminum energy consumption on the basis of smooth operation of the electrolytic cell. However, there are many parameters of the aluminum electrolytic cell, and the parameters are nonlinear and strongly coupled, which brings great difficulty to the modeling of the aluminum electrolytic production process. The recurrent neural network has a strong nonlinear mapping ability and is suitable for Solve the nonlinear system modeling problem, and pr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More