TURBO GENERATOR SYSTEM IDENTIFICATION USING GENETIC ALGORITHM

المؤلفون

  • Sahar R. Alsakini Electromechanical Engineering Department, University of Technology, Baghdad, Iraq مؤلف
  • Ahmed T. Alobaidi Computer Sciences Department, University of Technology, Baghdad, Iraq مؤلف
  • Ahmed J. Sultan College of Electrical and Electronic Techniques, Baghdad, Iraq مؤلف

الكلمات المفتاحية:

Turbogenerator، Genetic Algorithm، Optimization identification، Chromosome، Crossover point

الملخص

The turbogenerator is one of the mean important parts of the thermal power station, which is the most famous used as a generation power plant since the serving of electricity till now. The turbogenerator unit behavior is a non-linear and complicated system, for this causation, the identification models are used for the best and close optimization to have the highest and most accurate controller. In this paper, we will use the conjunction of data by intelligence techniques called "Genetic algorithm" to have the optimum behavior without using complex mathematical equations. The result we have from the genetic algorithm is showing the capability to reach the highest accuracy in system work identity, which are dependent on real data registered from no-load in the second unit of the Mussiab thermal power station.

التنزيلات

Key Dates

منشور

2016-11-01

إصدار

مجلد 20 عدد 6 (2016): Journal of Engineering and Sustainable Development

القسم

Articles

الرخصة

Creative Commons License

هذا العمل مرخص بموجب Creative Commons Attribution 4.0 International License.

The Journal of Engineering and Sustainable Development is an open-access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowed to search, download, share, distribute, print, or link to the full texts of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article.
Creative Commons-Attribution (BY)

كيفية الاقتباس

TURBO GENERATOR SYSTEM IDENTIFICATION USING GENETIC ALGORITHM. (2016). مجلة الهندسة والتنمية المستدامة, 20(6), 12-31. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/695

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