Application of lyapunov-based adaptive neural network UPFC damping controllers for transient stability enhancement

IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES

Volumn , Issue , 2008, Pages

  Chu, Chia Chi ^a,b   Tsai, Hung Chi ^a,c  

^a IEEE

^b NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^c CHANG GUNG UNIVERSITY   (Taiwan)

Author keywords

Back propagation; Energy functions; FACTS; Recurrent neural network; Transient stability; UPFC

Indexed keywords

ADAPTIVE SYSTEMS; APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; BACKPROPAGATION ALGORITHMS; CHLORINE COMPOUNDS; CONTROL SYSTEM ANALYSIS; CONTROL SYSTEMS; CONTROL THEORY; DAMPING; ELECTRIC CONTROL EQUIPMENT; ELECTRIC POWER SYSTEM INTERCONNECTION; ELECTRIC POWER SYSTEMS; ELECTRIC POWER TRANSMISSION NETWORKS; ENERGY CONVERSION; IMAGE CLASSIFICATION; MODEL STRUCTURES; NEURAL NETWORKS; PARAMETER ESTIMATION; POTENTIAL ENERGY; POTENTIAL ENERGY SURFACES; POWER TRANSMISSION; RECURRENT NEURAL NETWORKS; SYSTEM STABILITY; TELECOMMUNICATION NETWORKS; UNCERTAINTY ANALYSIS;

21ST CENTURY; ADAPTIVE NEURAL NETWORKS; BACK PROPAGATION; CONTROL PARAMETERS; CONTROL STRATEGIES; CORRESPONDING WEIGHTS; DAMPING CONTROL; DAMPING CONTROLLERS; DYNAMICAL CHARACTERISTICS; DYNAMICAL MODELING; ELECTRICAL ENERGY; ENERGY FUNCTIONS; EQUIVALENT MODELING; FACTS; INTERCONNECTED POWER SYSTEMS; LYAPUNOV; LYAPUNOV CONTROL; MODEL UNCERTAINTIES; NEURAL-NETWORK APPROXIMATIONS; POWER SWINGS; POWER SYSTEM MODELLING; POWER SYSTEMS; REAL TIME; RECURRENT NEURAL NETWORK; SHUNT SUSCEPTANCE; SIMULATION RESULTS; SYSTEM CONDITIONS; TRANSIENT STABILITY; UNIFIED-POWER-FLOW-CONTROLLER; UPFC;

ADAPTIVE CONTROL SYSTEMS;

EID: 52349115832     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PES.2008.4596580     Document Type: Conference Paper

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