EAF carrying energy optimization based on the genetic algorithm

AI Li-xiang; WANG Hong-bing; XU An-jun; DU Xi

doi:10.13374/j.issn1001-053x.2012.04.014

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AI Li-xiang, WANG Hong-bing, XU An-jun, DU Xi. EAF carrying energy optimization based on the genetic algorithm[J]. Chinese Journal of Engineering, 2012, 34(4): 450-456. doi: 10.13374/j.issn1001-053x.2012.04.014

Citation:

AI Li-xiang, WANG Hong-bing, XU An-jun, DU Xi. EAF carrying energy optimization based on the genetic algorithm[J]. Chinese Journal of Engineering, 2012, 34(4): 450-456. doi: 10.13374/j.issn1001-053x.2012.04.014

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EAF carrying energy optimization based on the genetic algorithm

doi: 10.13374/j.issn1001-053x.2012.04.014

1. School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China;
2. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China;
3. School of Computer Science and Technology, Anhui University, Hefei 230601, China

Received Date: 2011-02-22
Available Online: 2021-07-30

Abstract

Abstract

A carrying energy optimization model of an electric arc furnace(EAF) was proposed by introducing an energy carrier and considering the factors of EAF charging structures,oxygen supply,carbon addition and power supply.Due to the complexity of its constraints,the model could not be solved by linear programming.In this paper the model was solved by a genetic algorithm.The energy values of BH1H,BHDDQ and SUS304 steels were calculated by the model.The results showed that under the premise of ensuring the indicators of EAF molten steel such as chemical composition,temperature and slag basicity to meet the requirements,the energy values of the molten steel in each furnace were reduced by 22.8%,21.4% and 23.6% for BH1H,BHDDQ and SUS304 steels,respectively.
- stainless steel,
- electric furnaces,
- energy utilization,
- optimization,
- genetic algorithms