Genetic algorithms to determine the critical values of a power energy system for different operating conditions

Energy Education Science and Technology Part A: Energy Science and Research

Volumn 28, Issue 2, 2012, Pages 971-982

  Kandara, Osman ^a   Ozturk, Ali ^b  

^a SOUTHERN UNIVERSITY   (United States)

^b DUZCE UNIVERSITY   (Turkey)

Author keywords

Artificial Intelligence; Genetic algorithms; Newton Raphson; Power Distribution; Power system stability

Indexed keywords

ACTIVE POWER; ARTIFICIAL INTELLIGENCE METHODS; BASE SYSTEMS; CRITICAL VALUE; LOAD BUS VOLTAGE; NEWTON-RAPHSON; OPERATING CONDITION; POWER DISTRIBUTIONS; POWER ENERGY; POWER SYSTEM STABILITY; SHUNT COMPENSATION;

ARTIFICIAL INTELLIGENCE; SYSTEM STABILITY;

GENETIC ALGORITHMS;

EID: 84861967499     PISSN: 1308772X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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