Application of Bat Algorithm to Optimize Scaling Factors of Fuzzy Logic-Based Power System Stabilizer for Multimachine Power System

2016 ◽  
Vol 17 (1) ◽  
pp. 41-53 ◽  
Author(s):  
D. K. Sambariya ◽  
R. Prasad
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Controller ◽  
Nonlinear Models ◽  
Bat Algorithm ◽  
Test System ◽  
Power System Stabilizer ◽  
Scaling Factors ◽  
Test Power ◽  
System Stabilizer

AbstractThis article presents the design of optimized fuzzy logic-based power system stabilizer (FPSS) to enhance small signal stability using bat algorithm (BA). The proposed optimization of scaling factors of FPSS is considered with an objective function based on square error minimization to guarantee the stability of nonlinear models of test system using BA. The BA-optimized FPSS (BAFPSS) controller is applied to the standard IEEE ten-machine thirty-nine-bus test power system model in the decentralized manner, and the performance is compared with the robust fuzzy controller. The robustness is tested by considering four different models of the test power system with different fault locations to establish the superiority of the proposed BAFPSS over the FPSS.

Robust adaptive fuzzy logic power system stabilizer

2009 ◽  
Vol 36 (10) ◽  
pp. 12104-12112 ◽  
Author(s):  
T. Hussein ◽  
M.S. Saad ◽  
A.L. Elshafei ◽  
A. Bahgat
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Power System Stabilizer ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic ◽  
Robust Adaptive ◽  
System Stabilizer

scholarly journals Dynamic Stability and Analysis of SMIB system with FLC Based PSS including Load Damping Parameter Sensitivity

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Jagadeesh Pothula ◽  
Ch. Durga Prasad ◽  
M. Sai Veerraju
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Dynamic Analysis ◽  
Single Machine ◽  
Fuzzy Logic Controller ◽  
Parameter Sensitivity ◽  
Power System Stabilizer ◽  
Pid Controllers ◽  
Damping Parameter ◽  
System Stabilizer

This paper studies Dynamic Analysis and Stability of Single machine connected to infinite bus (SMIB) with power system stabilizer (PSS) in presence of Fuzzy logic controller (FLC) including load damping parameter sensitivity. Here PSS is modeled using fuzzy logic controller and the response is compared with the responses of the system in presence of conventional PI, PID controllers including load damping parameters sensitivity. In case of FLC based PSS the responses are compared different load damping parameters. Matlab-Simulink is used to test the results.

scholarly journals Bat Intelligence For Tunning Power System Stabilizer At Barru Power Plant

2018 ◽  
Vol 2 (1) ◽  
pp. 16-20
Author(s):  
Muhammad Ruswandi Djalal ◽  
Andareas Pangkung ◽  
Sonong Sonong ◽  
Apollo Apollo
Keyword(s):  
Power Plant ◽  
Power System ◽  
Dynamic Stability ◽  
Bat Algorithm ◽  
System Dynamic ◽  
Power System Stabilizer ◽  
Rotor Angle ◽  
System Stabilizer ◽  
Smart Computing

Changes in load on the power system suddenly, can cause dynamic disruption. This disturbance can not be responded well by the generator, so it can affect the system dynamic stability, such as the occurrence of oscillation speed and rotor angle. Conventional control of excitation and governor, also unable to repair the oscillations, so that additional controllers such as Power System Stabilizer (PSS) are required. In the use of PSS, there are several problems that often arise, namely the correct tuning of PSS parameters. In this research, we proposed a method of smart computing based on bat algorithm, for tuning PSS parameters. From the analysis results can be concluded, the performance performance of generator barru increased with the installation of Power System Stabilizer with optimal PSS parameter, with parameters respectively Kpss = 44.0828, T1 = 0.0284, T2 = 0.0146, T3 = 0.7818, T4 = 1.2816.

Speaker-Independent Malay Syllable Recognition Using Singular and Modular Neural Networks

2012 ◽  
Author(s):  
Hua Nong Ting ◽  
Jasmy Yunus ◽  
Sheikh Hussain Shaikh Salleh
Keyword(s):  
Power System ◽  
Fuzzy Inference ◽  
Design Procedure ◽  
Test System ◽  
Power System Stabilizer ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Input Signals ◽  
System Stabilizer

This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro–fuzzy inference system (ANFIS) and investigates their robustness for a multi–machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four–machine and a two–area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead–lag based power system stabilizer controller.

Designing Power System Stabilizer for Multimachine Power System Using Neuro-Fuzzy Algorithm

2012 ◽  
Author(s):  
M.F. Othman ◽  
M. Mahfouf ◽  
D.A. Linkens
Keyword(s):  
Power System ◽  
Fuzzy Inference ◽  
Design Procedure ◽  
Test System ◽  
Power System Stabilizer ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Input Signals ◽  
System Stabilizer

This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro–fuzzy inference system (ANFIS) and investigates their robustness for a multi–machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four–machine and a two–area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead–lag based power system stabilizer controller.

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