Fopid based AGC with PSO
Ch. M. S. N. V Sri Sai1, Muzeeb Khan Patan2, Md. Azahar Ahmed3
1Ch M S N V Sri Sai, Department of Electrical and Electronics Engineering, SRKR Engineering College (A), Bhimavaram (Andhra Pradesh), India.
2Muzeeb Khan Patan, Department of Electrical and Electronics Engineering, SRKR Engineering College (A), Bhimavaram (Andhra Pradesh), India.
3Md. Azahar Ahmed, Department of Electrical and Electronics Engineering, SRKR Engineering College (A), Bhimavaram (Andhra Pradesh), India.
Manuscript received on 16 May 2019 | Revised Manuscript received on 10 June 2019 | Manuscript Published on 15 June 2019 | PP: 370-375 | Volume-8 Issue-1S3 June 2019 | Retrieval Number: A10670681S319/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper explores the analysis of three area interconnected power system by employing optimization techniques to the Automatic Generation Control (AGC) for adjusting of controller parameters of FOPID controller. Here, FOPID controller is taken to diminish the integral time multiplied absolute error (ITAE). Furthermore, the control strategy is verified by Particle Swarm Optimization (PSO) algorithm to test the settling time and peak over shoots values and their contrast with conventional IOPID Controller. The optimal values of the controller are achieved by taking performance measure index as the integral time multiplied absolute error (ITAE) and it is minimized through PSO algorithm. We can observe that the settling time of PID controller with PSO is greater than the FOPID controller with PSO.FOPID controller with PSO is more advantageous than PID controller with PSO .We can also apply the another optimization technique like sine cosine algorithm (SCA) on two area system and all the simulation results are obtained from MATLAB/SIMULINK.
Keywords: Fractional Order PID Controller (FOPID); Particle Swarm Optimization (PSO); Automatic Generation Control(AGC);.
Scope of the Article: Swarm Intelligence