Estimation of load model parameters from instantaneous voltage and current

P. Regulski; F. Gonzalez-Longatt; V. Terzija

doi:10.1109/FUZZY.2011.6007609

Estimation of load model parameters from instantaneous voltage and current

P. Regulski, F. Gonzalez-Longatt, V. Terzija

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Abstract

Load modeling is a very important aspect of voltage stability analysis as load characteristics governs voltage behavior. In this paper a compact solution to extract parameters of a load model is presented, which includes estimation of power components based on Improved Recursive Newton Type Algorithm and estimation of parameters of a dynamic Load Model using Genetic Algorithms. The paper demonstrates the influence of the preprocessing of the instantaneous values on the final estimation of load parameters. All tests were carried out using 9-buses P.M. Anderson system built in DIgSILENT. © 2011 IEEE.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems\|IEEE Int Conf Fuzzy Syst
Pages	164-169
Number of pages	5
DOIs	https://doi.org/10.1109/FUZZY.2011.6007609
Publication status	Published - 2011
Event	2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei Duration: 1 Jul 2011 → …

Conference

Conference	2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
City	Taipei
Period	1/07/11 → …

Keywords

genetic algorithm
load modeling
parameter estimation
power components

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10.1109/FUZZY.2011.6007609

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title = "Estimation of load model parameters from instantaneous voltage and current",

abstract = "Load modeling is a very important aspect of voltage stability analysis as load characteristics governs voltage behavior. In this paper a compact solution to extract parameters of a load model is presented, which includes estimation of power components based on Improved Recursive Newton Type Algorithm and estimation of parameters of a dynamic Load Model using Genetic Algorithms. The paper demonstrates the influence of the preprocessing of the instantaneous values on the final estimation of load parameters. All tests were carried out using 9-buses P.M. Anderson system built in DIgSILENT. {\textcopyright} 2011 IEEE.",

keywords = "genetic algorithm, load modeling, parameter estimation, power components",

author = "P. Regulski and F. Gonzalez-Longatt and V. Terzija",

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language = "English",

isbn = "9781424473175",

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AU - Regulski, P.

AU - Gonzalez-Longatt, F.

AU - Terzija, V.

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AB - Load modeling is a very important aspect of voltage stability analysis as load characteristics governs voltage behavior. In this paper a compact solution to extract parameters of a load model is presented, which includes estimation of power components based on Improved Recursive Newton Type Algorithm and estimation of parameters of a dynamic Load Model using Genetic Algorithms. The paper demonstrates the influence of the preprocessing of the instantaneous values on the final estimation of load parameters. All tests were carried out using 9-buses P.M. Anderson system built in DIgSILENT. © 2011 IEEE.

KW - genetic algorithm

KW - load modeling

KW - parameter estimation

KW - power components

U2 - 10.1109/FUZZY.2011.6007609

DO - 10.1109/FUZZY.2011.6007609

M3 - Conference contribution

SN - 9781424473175

SP - 164

EP - 169

BT - IEEE International Conference on Fuzzy Systems|IEEE Int Conf Fuzzy Syst

T2 - 2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011

Y2 - 1 July 2011

ER -

Estimation of load model parameters from instantaneous voltage and current

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Keywords

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