Stability Enhancement of TLBO Tuned SMIB System
Kapil Parkh1, Vinesh Agarwal2

1Kapil Parkh*, Department of Electrical Engineering, Sangam University, India.
2Dr. Vinesh Agarwal, Department of Electrical Engineering, Sangam University, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1389-1398 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7744038620 /2020©BEIESP | DOI: 10.35940/ijrte.F7744.038620

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Abstract: In this paper investigation of the application of teaching learning based optimization (TLBO) technique for the design of a modified Phillips haffron model of SMIB installed with SSSC based controller is made. The design objectives are to reduce low frequency oscillation and improve power system stability. Simulation result are demonstrated with Eigen value analysis, where various types of disturbance is applied as mechanical torque input and reference voltage settling, variation in parameter & various loading condition. The results obtained are compared with some well-known optimization techniques, such as the genetic algorithm (GA), particle swarm optimization (PSO) and the gravitational search algorithm (GSA). A comparative study of results demonstrates that the results of the proposed controller were more precise and robust
Keywords: Single Machine Infinite Bus (SMIB); Modified Phillips Haffron Model; Static Synchronous Series Compensator (SSSC); Teaching Learning Based Algorithm (TLBO); Eigen Value Analysis.
Scope of the Article: Analysis Of Algorithms And Computational Complexity.