Identification of Dynamic Load Model Parameters Using Particle Swarm Optimization

Hwa Chang Song

doi:10.5391/IJFIS.2010.10.2.128

Identification of Dynamic Load Model Parameters Using Particle Swarm Optimization

Hwa Chang Song

Dept. of Electrical and Information Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

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

Original language	English
Pages (from-to)	128-133
Number of pages	6
Journal	International Journal of Fuzzy Logic and Intelligent Systems
Volume	10
Issue number	2
DOIs	https://doi.org/10.5391/IJFIS.2010.10.2.128
State	Published - Jun 2010

Access to Document

10.5391/IJFIS.2010.10.2.128

Cite this

@article{b6efa56539c346dc8179de966b3accaf,

title = "Identification of Dynamic Load Model Parameters Using Particle Swarm Optimization",

abstract = "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",

author = "Song, \{Hwa Chang\}",

year = "2010",

month = jun,

doi = "10.5391/IJFIS.2010.10.2.128",

language = "English",

volume = "10",

pages = "128--133",

journal = "International Journal of Fuzzy Logic and Intelligent Systems",

issn = "1598-2645",

publisher = "한국지능시스템학회",

number = "2",

}

TY - JOUR

T1 - Identification of Dynamic Load Model Parameters Using Particle Swarm Optimization

AU - Song, Hwa Chang

PY - 2010/6

Y1 - 2010/6

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

U2 - 10.5391/IJFIS.2010.10.2.128

DO - 10.5391/IJFIS.2010.10.2.128

M3 - Article

SN - 1598-2645

VL - 10

SP - 128

EP - 133

JO - International Journal of Fuzzy Logic and Intelligent Systems

JF - International Journal of Fuzzy Logic and Intelligent Systems

IS - 2

ER -

Identification of Dynamic Load Model Parameters Using Particle Swarm Optimization

Abstract

Access to Document

Fingerprint

Cite this