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The Optimization of the Power Supply Curve for Electric Arc Furnace Based on Genetic Algorithm

Author: SunMingQiang
Tutor: MaoZhiZhong
School: Northeastern University
Course: Control Theory and Control Engineering
Keywords: Electric arc furnace Supply curve Genetic Algorithms Constraint handling Hybrid coding
CLC: TM924.4
Type: Master's thesis
Year: 2008
Downloads: 64
Quote: 0
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Abstract


Reasonable power supply strategy in the electric arc furnace steelmaking process , not only to ensure the smooth progress of the operation , but also helps to reduce power consumption , electrode wear and erosion of the furnace wall , shorten the refining cycle and bring good economic benefits . Consult on the basis of a large number of domestic and foreign literature , combined with the electrical characteristics of the modern electric arc the nonlinear reactance model regression analysis based on field data , and in -depth study of electric arc furnace electric characteristics and the smelting process energy conservation foundation established on the arc furnace powered model based on economic indicators , the model to a ton of steel , power consumption smallest , of smelting the shortest and electrode consumption minimum target to achieve overall optimization of the electric arc furnace power supply system . Arc furnace powered model based on economic indicators is a constrained multi-objective mixed integer nonlinear programming problem , comparing the advantages and shortcomings of the traditional optimization methods and genetic algorithm to solve this kind of problem , the paper proposes a genetic algorithm for constraint handling NSGA-Ⅱ algorithm and hybrid coding oriented constraint handling genetic algorithm to solve the constraint is difficult to deal with the problem , hybrid coding NSGA-Ⅱ algorithm to solve mixed integer variables and multi-objective problem. Then these two algorithms implemented in C . Last 3 # arc furnace of a steel mill in Shanghai as the background , the application of constraint-oriented processing of genetic algorithms and hybrid coding NSGA-Ⅱ algorithm to solve the electric arc furnace powered model , and simulation results are analyzed to develop a the reasonable supply curve . In addition, the optimization algorithm is applied to the actual article also designed according to the architecture of the electric arc furnace control system of the electric arc furnace supply curve optimization software .

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CLC: > Industrial Technology > Electrotechnical > Electrification,electrical energy application > Electric heating > Electric arc furnace
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