Load Frequency Control of Multi Area Power System using Different Intelligent Controllers
Anoop Kumar Singh1, Sudhir Kumar Srivastava2, Vikas Pandey3
1Anoop Kumar Singh, M.Tech. Student, Madan Mohan Malviya Engineering College, Gorakhpur, (Uttar Pradesh), India.
2Sudhir Kumar Srivastava, Associate Prof, Department of Electrical Engineering, Madan Mohan Malviya Engineering College, Gorakhpur, (Uttar Pradesh), India.
3Vikas Pandey, Assistant Professor, Department of Electrical Engineering, BBD Group, Lucknow,(Uttar Pradesh).India.
Manuscript received on January 10, 2016. | Revised Manuscript received on January 13, 2016. | Manuscript published on January 15, 2016. | PP: 28-32 | Volume-4 Issue-2, January 2016. | Retrieval Number: B0960014216/2016©BEIESP
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© The Authors. Published By: 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: In power system engineering exact load prediction is difficult task because a continuous load changing in power systems network that disturb the frequency directly. If the frequency is deviate from its limit, there show a severe effect on power system. So load frequency controller (LFC) is designed and if it working properly, the frequency is quickly returned to the normal operating point that means steady state error become zero. There are two types of controllers used in this paper which are Fuzzy controllers and GA-PID (pid controller tuned by genetic algorithm) controllers. The performance of GA-PID controller is quite fast and efficient. The result shows an improved performance in terms of rise time, settling time, steady state error and overshoot. In this paper we use linear single area (thermal) and two area (thermal-thermal) model for simplification. The effectiveness of the proposed controller is confirmed via extensive study using MATLAB/SIMULINK software. Simulation results are carried out by 10% system disturbances in both of one and two areas power system.
Keywords: Fuzzy controller, genetic algorithm, load frequency control, PID controller.