DocumentCode :
3195056
Title :
PSO based optimal PI tunning of AHCC D-STATCOM
Author :
Pudi, Vasudeva Naidu ; Banakara, Basavaraja
Author_Institution :
Electr. & Electron. Eng., GITAM Univ., Hyderabad, India
fYear :
2015
fDate :
20-22 May 2015
Firstpage :
215
Lastpage :
220
Abstract :
This paper presents a design of adaptive hysteresis current controller (AHCC) by optimal tuning of PI regulator using PSO technique for a distribution static compensator (D-STATCOM). It is desirable to have optimal values of Kp and Ki in a PI regulator to decreases steady state error and improve stability of the system. This generates accurate values of reference injected currents and compare with instantaneous injected currents with help of AHCC in D-STATCOM. Hence to mitigate the source current harmonics and to improve the power quality in distribution system under different load considerations. The dynamic model of D-STATCOM has been adopted with AHCC by using MATLAB/Simulink. The optimal value Kp and Ki in a PI regulator are computed using particle swarm optimization (PSO) technique and the results are verified by genetic algorithm (GA). The simulations result show that the proposed PSO technique gives minimum error and optimally chosen parameters of PI, as compared to GA technique.
Keywords :
PI control; adaptive control; electric current control; genetic algorithms; harmonics suppression; optimal control; particle swarm optimisation; power distribution control; power supply quality; power system stability; static VAr compensators; AHCC D-STATCOM; GA; PSO based optimal PI regulator tunning; adaptive hysteresis current controller; distribution static compensator; distribution system stability; genetic algorithm; particle swarm optimization; power quality improvement; source current harmonic mitigation; Automatic voltage control; Genetic algorithms; Hysteresis; Power harmonic filters; Regulators; Switches; Adaptive Hysteresis current Controller (AHCC); Distribution static compensator (D-STATCOM); Genetic Algorithm (GA); Optimization techniques (OT); Particle Swarm Optimization (PSO); Simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Power Engineering (EPE), 2015 16th International Scientific Conference on
Conference_Location :
Kouty nad Desnou
Type :
conf
DOI :
10.1109/EPE.2015.7161063
Filename :
7161063
Link To Document :
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