TY - JOUR
T1 - Cuckoo search algorithm for optimal placement and sizing of static var compensator in large-scale power systems
AU - Nguyen, Khai Phuc
AU - Fujita, Goro
AU - Dieu, Vo Ngoc
PY - 2016
Y1 - 2016
N2 - This paper presents an application of Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator. Cuckoo search algorithm is a modern heuristic technique basing Cuckoo species' parasitic strategy. The Lévy flight has been employed to generate random Cuckoo eggs. Moreover, the objective function is a multi objective problem, which minimizes loss power, voltage deviation and investment cost of Static VAR Compensator while satisfying other operating constraints in power system. Cuckoo search algorithm is evaluated on three case studies and compared with the Teaching-learning-based optimization, Particle Swarm optimization and Improved Harmony search algorithm. The results show that Cuckoo search algorithm is better than other optimization techniques and its performance is also better.
AB - This paper presents an application of Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator. Cuckoo search algorithm is a modern heuristic technique basing Cuckoo species' parasitic strategy. The Lévy flight has been employed to generate random Cuckoo eggs. Moreover, the objective function is a multi objective problem, which minimizes loss power, voltage deviation and investment cost of Static VAR Compensator while satisfying other operating constraints in power system. Cuckoo search algorithm is evaluated on three case studies and compared with the Teaching-learning-based optimization, Particle Swarm optimization and Improved Harmony search algorithm. The results show that Cuckoo search algorithm is better than other optimization techniques and its performance is also better.
KW - Cuckoo search algorithm
KW - FACTS
KW - Optimal placement and sizing
KW - Optimal power flow
KW - Shunt VAR compensator
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U2 - 10.1515/jaiscr-2016-0006
DO - 10.1515/jaiscr-2016-0006
M3 - Article
AN - SCOPUS:85009804097
SN - 2083-2567
VL - 6
SP - 59
EP - 68
JO - Journal of Artificial Intelligence and Soft Computing Research
JF - Journal of Artificial Intelligence and Soft Computing Research
IS - 2
ER -