Neural identification of SSSC based on average model using GAMMA, DNN, RBF and MLP for steady state calculations

2009 IEEE Bucharest PowerTech: Innovative Ideas Toward the Electrical Grid of the Future

Volumn , Issue , 2009, Pages

  Bina, M Tavakoli ^a   Viki, A Houshmand ^a   Rahimzadeh, Sajad ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Averaging technique; FACTS devices; Modeling; Neural network

Indexed keywords

AVERAGE MODEL; AVERAGING TECHNIQUE; CONGESTION MANAGEMENT; DESIGN AND DEVELOPMENT; DEVELOPED MODEL; ELECTRICAL ENERGY; EXACT SOLUTION; FACTS DEVICES; HIGH-FREQUENCY SWITCHING; NEURAL IDENTIFICATION; NEURAL MODELS; POWER MARKETS; POWER SYSTEM APPLICATIONS; POWER SYSTEM COMPONENTS; POWER SYSTEM STUDIES; POWER SYSTEMS; SIMPLE MODEL; STEADY STATE; STEADY STATE CALCULATIONS; SWITCHING BEHAVIORS; TIME-DOMAIN REPRESENTATION; TRANSMISSION SYSTEMS;

ELECTRIC IMPEDANCE; ELECTRIC POWER TRANSMISSION; ELECTRIC POWER TRANSMISSION NETWORKS; PROBLEM SOLVING; RADIAL BASIS FUNCTION NETWORKS; TIME DOMAIN ANALYSIS;

NEURAL NETWORKS;

EID: 74949137325     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PTC.2009.5282022     Document Type: Conference Paper

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