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“Coordination Of Adaptive Neuro Fuzzy Inference System (ANFIS) And Type-2 Fuzzy Logic System-Power System Stabilizer (T2FLS-PSS) To Improve A Large-scale Power System Stability” Metadata:

  • Title: ➤  Coordination Of Adaptive Neuro Fuzzy Inference System (ANFIS) And Type-2 Fuzzy Logic System-Power System Stabilizer (T2FLS-PSS) To Improve A Large-scale Power System Stability
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  • Internet Archive ID: 10.11591ijece.v8i1.pp76-86

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Intelligent control included ANFIS and type-2 fuzzy (T2FLS) controllers grown-up rapidly and these controllers are applied successfully in power system control. Meanwhile, small signal stability problem appear in a large-scale power system (LSPS) due to load fluctuation. If this problem persists, and can not be solved, it will develop blackout on the LSPS. How to improve the LSPS stability due to load fluctuation is done in this research by coordinating of PSS based on ANFIS and T2FLS. The ANFIS parameters are obtained automatically by training process. Meanwhile, the T2FLS parameters are determined based on the knowledge that obtained from the ANFIS parameters. Input membership function (MF) of the ANFIS is 5 Gaussian MFs. On the other hand, input MF of the T2FLS is 3 Gaussian MFs. Results show that the T2FLS-PSS is able to maintain the stability by decreasing peak overshoot for rotor speed and angle. The T2FLS-PSS makes the settling time is shorter for rotor speed and angle on local mode oscillation as well as on inter-area oscillation than conventional/ ANFIS-PSS. Also, the T2FLS-PSS gives better performance than the other PSS when tested on single disturbance and multiple disturbances.

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