Fuzzy power system stabilizer including a fuzzy PI controller

Ferreira, André; Barreiros, José Augusto Lima; Brito-de-Souza, Jorge Roberto

doi:10.1049/cp:19980342

“…Some new excitation controllers based on artificial neural networks were claimed to be effective for different operating points, but they required complex algorithms and a long time for training neural nets [9]. Fuzzy logic controllers have been used in design power system stabilizers [10]. This type of controllers does not require any kind of computational complexity, but it always needs a right off-line design.…”

Section: Introduction Of Generator Excitation Controlmentioning

confidence: 99%

Synchronous Generator Excitation Control Based on Model Predictive Control

Jin¹

2021

Preprint

0

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This thesis research has designed and developed an optimal predictive excitation control, named the Model Predictive Excitation Control (MPEC), for utility generators. Four significant results are achieved: First, the MPEC has been designed and has significantly improved the classical model predictive control and is much simpler and computationally efficient. Second, the MPEC simulation program and results have been accomplished, and study cases have demonstrated the effectiveness of the MPEC. Third, the Modified classical model predictive control procedure has been formulated to correct a timing error such that the controlling input for the present time is re-written as that for the next step. Fourth, the MPEC optimization formulation and procedure has been developed for the generator control with only two substation-ready-available measurements which are the generator terminal voltage and speed.

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“…Some new excitation controllers based on artificial neural networks were claimed to be effective for different operating points, but they required complex algorithms and a long time for training neural nets [9]. Fuzzy logic controllers have been used in design power system stabilizers [10]. This type of controllers does not require any kind of computational complexity, but it always needs a right off-line design.…”

Section: Introduction Of Generator Excitation Controlmentioning

confidence: 99%

Synchronous Generator Excitation Control Based on Model Predictive Control

Jin¹

2021

Preprint

0

View full text Add to dashboard Cite

This thesis research has designed and developed an optimal predictive excitation control, named the Model Predictive Excitation Control (MPEC), for utility generators. Four significant results are achieved: First, the MPEC has been designed and has significantly improved the classical model predictive control and is much simpler and computationally efficient. Second, the MPEC simulation program and results have been accomplished, and study cases have demonstrated the effectiveness of the MPEC. Third, the Modified classical model predictive control procedure has been formulated to correct a timing error such that the controlling input for the present time is re-written as that for the next step. Fourth, the MPEC optimization formulation and procedure has been developed for the generator control with only two substation-ready-available measurements which are the generator terminal voltage and speed.

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“…Moodley et al [8] investigated the effect of FLPSS in a multimachine environment. Ferreira et al [9] proposed a FPSS including a fuzzy PI controller to improve steady state behavior of a system. Lim [10] proposed a fuzzy logic control scheme using only one input signal which is derived as the linear combination of signal, signal derivative and signal integral.…”

Section: Introductionmentioning

confidence: 99%

Effect of Different Membership Functions on Fuzzy Power System Stabilizer for Synchronous Machine Connected to Infinite Bus

Touil

¹

,

Attous²

2013

IJCA

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The effectiveness of power system stabilizer (PSS) in providing damping and improving the dynamic response is well established. In this paper focuses, the performance of single machine infinite bus is studied with fuzzy power system stabilizer (FPSS). The generator is represented by the standard K-coefficients as second order system. The mechanism to discuss the rules is described and the performance is investigated for trapezoidal, triangular and Gaussian membership functions of input and output variables. For FPSS, speed deviation and acceleration deviation are taken as input. The system is simulated in SIMULINK environment and performance is investigated for transients due to change in input of varying magnitude.

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Fuzzy power system stabilizer including a fuzzy PI controller

Cited by 10 publications

References 0 publications

Synchronous Generator Excitation Control Based on Model Predictive Control

Synchronous Generator Excitation Control Based on Model Predictive Control

Synchronous Generator Excitation Control Based on Model Predictive Control

Effect of Different Membership Functions on Fuzzy Power System Stabilizer for Synchronous Machine Connected to Infinite Bus

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