Neural network predictive control of UPFC for improving transient stability performance of power system

Applied Soft Computing Journal

Volumn 11, Issue 8, 2011, Pages 4581-4590

  Tiwari, Sheela ^a   Naresh, Ram ^b   Jha, R ^a  

^a DR B R AMBEDKAR NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^b NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Identification; Neural networks; Power system transient stability; Predictive control; Unified power flow controller (UPFC)

Indexed keywords

BACKPROPAGATION LEARNING; CONTROL INPUTS; CONVENTIONAL-PI CONTROLLER; DAMPING PERFORMANCE; FASTER CONVERGENCE; GAUSS-NEWTON METHODS; LEVENBERG-MARQUARDT ALGORITHM; LINE SEARCH METHOD; MINIMIZATION ALGORITHMS; NEURAL NETWORK MODEL; OPERATING CONDITION; POWER SYSTEM TRANSIENT STABILITY; PREDICTIVE CONTROL; PREDICTIVE CONTROLLER; UNIFIED POWER FLOW CONTROLLERS;

BACKPROPAGATION ALGORITHMS; CONTROL SYSTEM STABILITY; CONTROLLERS; CONVERGENCE OF NUMERICAL METHODS; IDENTIFICATION (CONTROL SYSTEMS); NEURAL NETWORKS; NEWTON-RAPHSON METHOD; POWER TRANSMISSION;

ELECTRIC CONTROL EQUIPMENT;

EID: 80053576361     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.08.003     Document Type: Article

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