Performance evaluation of power system stabilizers based on Population-Based Incremental Learning (PBIL) algorithm

International Journal of Electrical Power and Energy Systems

Volumn 33, Issue 7, 2011, Pages 1279-1287

  Folly, Komla A ^a  

^a UNIVERSITY OF CAPE TOWN   (South Africa)

Author keywords

Electromechanical modes; Genetic algorithms (GAs); Population Based Incremental Learning (PBIL); Power system stabilizer (PSS)

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CROSSOVER OPERATOR; ELECTROMECHANICAL MODES; LARGE DISTURBANCE; MULTI MACHINE POWER SYSTEM; OPERATING CONDITION; PERFORMANCE EVALUATION; POPULATION-BASED INCREMENTAL LEARNING; POWER SYSTEM STABILIZER; POWER SYSTEM STABILIZERS; PROBABILITY VECTOR; PROBLEM REPRESENTATION; SIMULATION RESULT;

ELECTRIC POWER SYSTEMS; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; NEURAL NETWORKS; POWER TRANSMISSION; STANDBY POWER SYSTEMS;

LEARNING ALGORITHMS;

EID: 79960910981     PISSN: 01420615     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijepes.2011.05.004     Document Type: Article

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