DocumentCode :
622199
Title :
PID controller adjustment for MA-LFC by using Imperialist Competitive Algorithm
Author :
Soheilirad, M. ; Farzan, P. ; Othman, M.L. ; Karami, K. ; Hojabri, M.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Putra Malaysia, Serdang, Malaysia
fYear :
2013
fDate :
3-4 June 2013
Firstpage :
507
Lastpage :
512
Abstract :
In this paper a new evolutionary computing method based on Imperialist Competitive Algorithm (ICA) is used for tuning the elements of a PID controller which is applied in a Multi Area Load Frequency Control System (MA-LFC). If a large power imbalance is suddenly happened in a multi area power electric system, generation units and also consumer sides will be affected by the distortion in the energy balance between both two sides. This inequality is firstly handled by the kinetic energy of the system turning components, but, eventually, the frequency will change. Therefore, LFC is considered as one of the most challenging issues in power system control and operation. PID type controllers are conventional solutions for MA-LFC. The three parameters of the PID controllers have been adjusted traditionally. In this paper, a PID controller is applied for the MA-LFC problem and then its parts are modified by using ICA method. To validate the application of the technique, a multi area network with some uncertainties is provided. Finally the results of the ICAPID controller are compared with the ones of GA optimized controllers. The simulation results show the success and the validity of the ICA-PID controller in compare with the GA - PID controller.
Keywords :
evolutionary computation; frequency control; genetic algorithms; load regulation; three-term control; GA optimized controller; ICA; MA-LFC; PID controller adjustment; energy balance distortion; evolutionary computing method; genetic algorithm; imperialist competitive algorithm; kinetic energy; multiarea load frequency control system; multiarea power electric system; power generation unit; power system control; power system operation; system turning component; tuning; Conferences; Optimization; PD control; Performance analysis; Power engineering; Power systems; Reliability; Genetic Algorithm; Imperialist Competitive Algorithm; Load Frequency Control; Multi Area Network; Power System Dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2013 IEEE 7th International
Conference_Location :
Langkawi
Print_ISBN :
978-1-4673-5072-3
Type :
conf
DOI :
10.1109/PEOCO.2013.6564601
Filename :
6564601
Link To Document :
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