Kaiman filter based approach for ZIp load modeling for aggregate loads

Yiqi Zhang; Yuan Liao; Evan Jones; Nicholas Jewell; Dan M. Ionel

doi:10.1109/KPEC51835.2021.9446202

Kaiman filter based approach for ZIp load modeling for aggregate loads

Yiqi Zhang
, Yuan Liao
, Evan Jones
, Nicholas Jewell
, Dan M. Ionel

Producción científica: Conference contribution › revisión exhaustiva

5 Citas (Scopus)

Resumen

Constant impedance, constant current, constant power (ZIP) load modeling has been used in various power system applications. It is of great interest to accurately estimate Z I P parameters. This paper presents the Kaiman filtering based technique for estimating load Z I P parameters. In addition, aggregate load modeling is a common practice in utility companies. However, there are certain factors that can affect estimation results. This paper formulates the aggregate Z I P load modeling and provides insights into the effects of load connections and voltage unbalance on Z I P load modeling. The effects of voltage unbalance and load connection type on Z I P load estimation are illustrated through examples. Representative case studies based on the I E E E 34-bus system built in OpenDSS are reported.

Idioma original	English
Título de la publicación alojada	2021 IEEE Kansas Power and Energy Conference, KPEC 2021
ISBN (versión digital)	9781665441193
DOI	https://doi.org/10.1109/KPEC51835.2021.9446202
Estado	Published - 2021
Evento	2nd Annual IEEE Kansas Power and Energy Conference, KPEC 2021 - Manhattan, United States Duración: abr 19 2021 → abr 20 2021

Serie de la publicación

Nombre	2021 IEEE Kansas Power and Energy Conference, KPEC 2021

Conference

Conference	2nd Annual IEEE Kansas Power and Energy Conference, KPEC 2021
País/Territorio	United States
Ciudad	Manhattan
Período	4/19/21 → 4/20/21

Nota bibliográfica

Publisher Copyright:
© 2021 IEEE

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Affordable and clean energy

ASJC Scopus subject areas

Computer Networks and Communications
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Control and Optimization

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10.1109/KPEC51835.2021.9446202

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@inproceedings{26b2a95a4a194475bc15799efaea886a,

title = "Kaiman filter based approach for ZIp load modeling for aggregate loads",

abstract = "Constant impedance, constant current, constant power (ZIP) load modeling has been used in various power system applications. It is of great interest to accurately estimate Z I P parameters. This paper presents the Kaiman filtering based technique for estimating load Z I P parameters. In addition, aggregate load modeling is a common practice in utility companies. However, there are certain factors that can affect estimation results. This paper formulates the aggregate Z I P load modeling and provides insights into the effects of load connections and voltage unbalance on Z I P load modeling. The effects of voltage unbalance and load connection type on Z I P load estimation are illustrated through examples. Representative case studies based on the I E E E 34-bus system built in OpenDSS are reported.",

keywords = "Kaiman filter, Load model, Parameter estimation, ZIP load model",

author = "Yiqi Zhang and Yuan Liao and Evan Jones and Nicholas Jewell and Ionel, \{Dan M.\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2nd Annual IEEE Kansas Power and Energy Conference, KPEC 2021 ; Conference date: 19-04-2021 Through 20-04-2021",

year = "2021",

doi = "10.1109/KPEC51835.2021.9446202",

language = "English",

series = "2021 IEEE Kansas Power and Energy Conference, KPEC 2021",

booktitle = "2021 IEEE Kansas Power and Energy Conference, KPEC 2021",

}

Zhang, Y, Liao, Y, Jones, E, Jewell, N & Ionel, DM 2021, Kaiman filter based approach for ZIp load modeling for aggregate loads. En 2021 IEEE Kansas Power and Energy Conference, KPEC 2021. 2021 IEEE Kansas Power and Energy Conference, KPEC 2021, 2nd Annual IEEE Kansas Power and Energy Conference, KPEC 2021, Manhattan, United States, 4/19/21. https://doi.org/10.1109/KPEC51835.2021.9446202

TY - GEN

T1 - Kaiman filter based approach for ZIp load modeling for aggregate loads

AU - Zhang, Yiqi

AU - Liao, Yuan

AU - Jones, Evan

AU - Jewell, Nicholas

AU - Ionel, Dan M.

PY - 2021

Y1 - 2021

N2 - Constant impedance, constant current, constant power (ZIP) load modeling has been used in various power system applications. It is of great interest to accurately estimate Z I P parameters. This paper presents the Kaiman filtering based technique for estimating load Z I P parameters. In addition, aggregate load modeling is a common practice in utility companies. However, there are certain factors that can affect estimation results. This paper formulates the aggregate Z I P load modeling and provides insights into the effects of load connections and voltage unbalance on Z I P load modeling. The effects of voltage unbalance and load connection type on Z I P load estimation are illustrated through examples. Representative case studies based on the I E E E 34-bus system built in OpenDSS are reported.

AB - Constant impedance, constant current, constant power (ZIP) load modeling has been used in various power system applications. It is of great interest to accurately estimate Z I P parameters. This paper presents the Kaiman filtering based technique for estimating load Z I P parameters. In addition, aggregate load modeling is a common practice in utility companies. However, there are certain factors that can affect estimation results. This paper formulates the aggregate Z I P load modeling and provides insights into the effects of load connections and voltage unbalance on Z I P load modeling. The effects of voltage unbalance and load connection type on Z I P load estimation are illustrated through examples. Representative case studies based on the I E E E 34-bus system built in OpenDSS are reported.

KW - Kaiman filter

KW - Load model

KW - Parameter estimation

KW - ZIP load model

UR - https://www.scopus.com/pages/publications/85116083403

UR - https://www.scopus.com/pages/publications/85116083403#tab=citedBy

U2 - 10.1109/KPEC51835.2021.9446202

DO - 10.1109/KPEC51835.2021.9446202

M3 - Conference contribution

AN - SCOPUS:85116083403

T3 - 2021 IEEE Kansas Power and Energy Conference, KPEC 2021

BT - 2021 IEEE Kansas Power and Energy Conference, KPEC 2021

T2 - 2nd Annual IEEE Kansas Power and Energy Conference, KPEC 2021

Y2 - 19 April 2021 through 20 April 2021

ER -

Kaiman filter based approach for ZIp load modeling for aggregate loads

Resumen

Serie de la publicación

Conference

Nota bibliográfica

ODS de las Naciones Unidas

ASJC Scopus subject areas

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