Adaptive Neuro-fuzzy SVC for Multimachine Hybrid Power System Stability Improvement with a Long of Double Circuit Transmission Lines

Jaipradidtham, Chamni

doi:10.1007/11427469_106

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…In order to correspond with these demands, controllers with static var compensators (SVCs) are used. Some of these controllers are neuro-fuzzy SVCs [1,2], fuzzy-proportional-integral-derivative (PID) controllers [3,4], nonlinear and H ∞ controls [5,6], adaptive controls [7] and intelligent controllers [8], fuzzy logic [9,10] optimal predictive controllers [11], and nonlinear and nonlinear robust controllers [12,13].…”

Section: Introductionmentioning

confidence: 99%

Control of SVC based on the sliding mode control method

Köse¹,

Kizmaz²,

Abacı³

et al. 2014

Turk J Elec Eng & Comp Sci

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Abstract:A genetic algorithm (GA)-based sliding mode controller is proposed to improve the voltage stability of a power system with a static var compensator. The proposed controller is examined for improving the load bus voltage, which changes under different demanding powers, and its performance for transient analysis is compared with the ZieglerNichols proportional-integral (ZNPI), Lyapunov-based sliding mode control (LASMC), and GA-based proportionalintegral-derivative (GAPID) controllers. The dynamic equations, consisting of a 2-bus nonlinear system, are converted to a mathematical description of sliding mode techniques. The optimum values of the sliding mode controller and proportional-integral-derivative (PID) coefficients that are required are calculated using the GA technique. Output voltage performances are obtained based on the demanding powers, which are at a constant variation. In this process, sliding mode, ZNPI, GAPID, and LASMC controllers are preferred in order to control the system. The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.

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Section: Introductionmentioning

confidence: 99%

Control of SVC based on the sliding mode control method

Köse¹,

Kizmaz²,

Abacı³

et al. 2014

Turk J Elec Eng & Comp Sci

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“…In order to get the performance of SVC devices increased, various control techniques are used. Some of these controllers are Neuro-Fuzzy Static Var Compensator [3], fuzzy-PID controller [4], adaptive controller [5], intelligent controller [6], fuzzy logic controller [7], and non-linear robust controller [8] respectively.…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control Based on Genetic Algorithm for WSCC Systems Include of SVC

Köse

Abacı

Kizmaz

et al. 2013

ElAEE

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In this study, in order to control the voltage of the Western System Coordinating Council (WSCC) system, a sliding mode control has been used. First, the active and reactive power values, voltage and angle values of the loadbuses have been calculated. The load-buses which their voltage levels are lower than 1 pu has been identified. After that, by considering one of these load-buses, the system is transformed to the system with two load-buses and the sliding mode control model has been obtained. The sliding mode parameters have been obtained by using genetic algorithm (GA) optimization technique. From the results of simulations of this model, it is shown that the voltage of the load-buses reaches at 1 pu with a very low error.

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