TY - GEN
T1 - Particle swarm optimization based load model parameter identification
AU - Kim, Young Gon
AU - Song, Hwachang
AU - Kim, Hong Rae
AU - Lee, Byongjun
PY - 2010
Y1 - 2010
N2 - This paper presents a method for estimating the parameters of dynamic models for induction motor dominating loads. Using particle swarm optimization, the method finds the adequate set of parameters that best fit the sampling data from the measurement for a period of time, minimizing the error of the outputs, active and reactive power demands and satisfying the steady-state error criterion.
AB - This paper presents a method for estimating the parameters of dynamic models for induction motor dominating loads. Using particle swarm optimization, the method finds the adequate set of parameters that best fit the sampling data from the measurement for a period of time, minimizing the error of the outputs, active and reactive power demands and satisfying the steady-state error criterion.
KW - Dynamic load model
KW - Parameter estimation
KW - Particle swarm optimization
KW - System identification
UR - http://www.scopus.com/inward/record.url?scp=78649577961&partnerID=8YFLogxK
U2 - 10.1109/PES.2010.5589394
DO - 10.1109/PES.2010.5589394
M3 - Conference contribution
AN - SCOPUS:78649577961
SN - 9781424483570
T3 - IEEE PES General Meeting, PES 2010
BT - IEEE PES General Meeting, PES 2010
T2 - IEEE PES General Meeting, PES 2010
Y2 - 25 July 2010 through 29 July 2010
ER -