Earlier detection of risk of blackout by real-time dynamic security assessment based on extreme learning machines

2010 International Conference on Power System Technology: Technological Innovations Making Power Grid Smarter, POWERCON2010

Volumn , Issue , 2010, Pages

  Xu, Y ^a   Dong, Z Y ^a   Meng, K ^a   Xu, Z ^a   Zhang, R ^a   Wu, Andrew Y ^a   Wong, K P ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Blackout prevention; Dynamic security assessment; Extreme learning machine (ELM); Intelligent system

Indexed keywords

ART MODEL; BLACKOUT PREVENTION; COMPLEX PARAMETER; COMPUTATION SPEED; COMPUTATION TIME; DATA MINING TECHNIQUES; DYNAMIC SECURITY ASSESSMENT; EXTREME LEARNING MACHINE; LEARNING SPEED; NEW ENGLAND; REAL-TIME DYNAMICS; REAL-TIME IMPLEMENTATIONS; SIMULATION RESULT; SITUATIONAL AWARENESS; STATE-OF-THE-ART METHODS; TEST SYSTEMS; TRAINING TIME;

DATA MINING; INNOVATION; INTELLIGENT SYSTEMS; LEARNING SYSTEMS; POWER GENERATION; RATING; REAL TIME CONTROL;

SECURITY OF DATA;

EID: 78751505413     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/POWERCON.2010.5666055     Document Type: Conference Paper

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