DocumentCode
604888
Title
An intelligent technique based on code algorithm for determination of optimum gain values of PID controller in an AGC system
Author
ChandraSekhar, K. ; Vaisakh, K.
Author_Institution
Dept. of Electr. Eng., Andhra Univ., Visakhapatnam, India
fYear
2013
fDate
1-2 March 2013
Firstpage
34
Lastpage
41
Abstract
Automatic generation control (AGC) of a power system provides power demand signals for power generators to control frequency and tie-line power flow due to the large load changes or other disturbances. Occurrence of large real power imbalance causes large frequency deviations from its nominal value which may be a threat to secure operation of power system. To avoid such situation, emergency control to maintain the system frequency using composite differential evolution (CODE) based proportional integral-derivative (PID) controller is proposed in this paper. CODE based optimum gains give better optimal transient response of frequency and tie line power changes compared to particle swarm optimization and classical DE based PID gains.
Keywords
emergency services; load flow control; power generation control; three-term control; transient response; AGC system; CODE-based optimum gains; CODE-based proportional integral-derivative controller; CoDE algorithm-based intelligent technique; PID controller; automatic generation control; classical DE-based PID gains; composite differential evolution; composite differential evolution-based PID controller; control frequency; emergency control; large frequency deviations; load changes; optimal frequency transient response; optimum gain values determination; particle swarm optimization; power demand signals; power generators; power system; power system secure operation; real power imbalance; system frequency; tie line power changes; tie-line power flow; Automatic generation control; Intelligent systems; Load flow; Optimization; Signal processing algorithms; Steady-state; Vectors; Automatic generation control; bilateral contracts; deregulation; differential evolution algorithm; optimization; particle swarm optimization; power system control;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems and Signal Processing (ISSP), 2013 International Conference on
Conference_Location
Gujarat
Print_ISBN
978-1-4799-0316-0
Type
conf
DOI
10.1109/ISSP.2013.6526870
Filename
6526870
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