TY - JOUR
T1 - Improving power system reliability calculation efficiency with EPSO variants
AU - Miranda, Vladimiro
AU - de Magalhaes Carvalho, Leonel
AU - da Rosa, Mauro Augusto
AU - da Silva, Armando M.L.
AU - Singh, Chanan
PY - 2009
Y1 - 2009
N2 - This paper presents an application of evolutionary particle swarm optimization (EPSO)-based methods to evaluate power system reliability. Population-based (PB) methods appear as competitors to the traditional Monte Carlo simulation (MCS), because they are computationally efficient in estimating a variety of reliability indices. The work reported in this paper demonstrates that EPSO variants can focus the search in the region of the state space where contributions to the formation of a reliability index may be found, instead of conducting a blind sampling of the space. The results obtained with EPSO are compared to MCS and with other PB methods.
AB - This paper presents an application of evolutionary particle swarm optimization (EPSO)-based methods to evaluate power system reliability. Population-based (PB) methods appear as competitors to the traditional Monte Carlo simulation (MCS), because they are computationally efficient in estimating a variety of reliability indices. The work reported in this paper demonstrates that EPSO variants can focus the search in the region of the state space where contributions to the formation of a reliability index may be found, instead of conducting a blind sampling of the space. The results obtained with EPSO are compared to MCS and with other PB methods.
KW - Evolutionary algorithms
KW - Monte Carlo sampling
KW - Particle swarm
KW - Population-based methods
KW - Reliability analysis
UR - http://www.scopus.com/inward/record.url?scp=70350738355&partnerID=8YFLogxK
U2 - 10.1109/TPWRS.2009.2030397
DO - 10.1109/TPWRS.2009.2030397
M3 - Article
AN - SCOPUS:70350738355
SN - 0885-8950
VL - 24
SP - 1772
EP - 1779
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 4
ER -