GA Technique to Solve the Load Frequency and Tie-Line Power Problem of Thermal Generating Unit
Advances in Networks
Volume 7, Issue 2, December 2019, Pages: 51-58
Received: Oct. 19, 2019; Accepted: Nov. 20, 2019; Published: Dec. 2, 2019
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Authors
Ashish Dhamanda, Electrical Engineering Department, Gurukula Kangri University, Haridwar, India
Gajendra Singh Rawat, Electrical Engineering Department, Gurukula Kangri University, Haridwar, India
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Abstract
For a wide role of a electric power system, Automatic Generation Control (AGC) is responsible to area load changes and abnormal imprecise system operating parameters essentially means very fast minimization of area frequency changes and mutual tie line power flow changes of the areas for satisfactory and stable operation of the system. Some technique gives the good results in normal operation but in abnormal condition, it take large time to settle down the load disturbance, which is harmful for the system. Genetic Algorithm (GA) Technique) provides better control performance over frequency deviations and tie line power flow deviations due to a normal and abnormal operating condition of sudden load changes. In this paper six area model of thermal generating units has been developed and simulated in MATLAB Simulink software. Response of the developed model has been obtained by GA technique and compared with the other technique like; fuzzy, PID. Tabulated result shows that the GA technique give the better performance over the other technique due to settling down the frequency and tie line power flow changing in less time and maintenance the system constancy with the litmits.
Keywords
Imprecise System, Frequency Deviations, Tie Line Power Flow, Automatic Generation Control, Genetic Algorithm
To cite this article
Ashish Dhamanda, Gajendra Singh Rawat, GA Technique to Solve the Load Frequency and Tie-Line Power Problem of Thermal Generating Unit, Advances in Networks. Vol. 7, No. 2, 2019, pp. 51-58. doi: 10.11648/j.net.20190702.16
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Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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