Analysis of synchronous generator stability in case of separate and self-excitation system

Mišković, Mato; Mirošević, Marija; Maljković, Zlatko

doi:10.1109/epepemc.2010.5606859

Cited by 3 publications

(1 citation statement)

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“…Interval type-2 fuzzy set is used to model uncertainty and imprecision in a better way. Interval type-2 fuzzy set is introduced at the first time at 1975 by Zadeh and developed by Mendel with characterizing interval type-2 fuzzy set as Footprint of Uncertainty (FOU) [24][25][26][27][28]. FOU is limited by superior and inferior type-1 membership function.…”

Section: Introductionmentioning

confidence: 99%

Excitation control of a power plant alternator using interval type-2 fuzzy logic controller

Sharma¹,

Pathak²,

Jha³

et al. 2018

AMA_C

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This paper presents a practical design of an intelligent type of controller using Interval Type-2 Fuzzy Logic Controller (IT2FLC) concepts for excitation control of a practical power generating system. This type of controller is suitable for real time operation and aims to improve the dynamic characteristics of the generating unit by acting properly on its original excitation system. The modeling of the power system under study consists of a synchronous generator connected via a transformer and a transmission line to an infinite bus. Next, digital simulations of the above system are performed using fuzzy control techniques that are based on previous work. The dynamic performances of the interval type-2 fuzzy logic controllers (IT2FLC) along with Interval type-1 Fuzzy logic controller in short FLC is presented by comparison using the integral square error criterion (ISE). Typical transient responses of the system are shown for comparison in order to demonstrate the effectiveness of the proposed controller. The computer simulation results obtained demonstrate clearly that the performance of the developed controller offers competitive damping effects on the generator oscillations, with respect to the associated ones of the FLC, over a wider range of operating conditions, while their hardware implementation is easier and the computational time needed for real-time applications is drastically reduced. In MATLAB/SIMULINK is simulated model of the synchronous generator connected to an AC system. A simple fuzzy logic control scheme is simulated for voltage control and generator stabilization.

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Section: Introductionmentioning

confidence: 99%