Online Static Load Model Estimation in Distribution Systems

Venkat Krishnan; Yingchen Zhang; Hongda Ren; Noel Schulz

doi:10.1109/ISIE.2019.8781530

Online Static Load Model Estimation in Distribution Systems

Venkat Krishnan, Yingchen Zhang, Hongda Ren, Noel Schulz

Power Systems Engineering

Washington State University

Research output: Contribution to conference › Paper

2 Scopus Citations

Abstract

This paper focuses on parameter identification for time-varying voltage-dependent polynomial load models in distribution systems - namely, the constant impedance (Z), constant current (I), and constant power (P). The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. The least-squares estimation method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations on the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system caused by varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data. Finally, the paper uses dynamic simulations data (synthetic high-resolution measurements) to further improve the estimation results.

Original language	American English
Pages	153-158
Number of pages	6
DOIs	https://doi.org/10.1109/ISIE.2019.8781530
State	Published - 2019
Event	2019 IEEE 28th International Symposium on Industrial Electronics (ISIE) - Vancouver, Canada Duration: 12 Jun 2019 → 14 Jun 2019

Conference

Conference	2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)
City	Vancouver, Canada
Period	12/06/19 → 14/06/19

Bibliographical note

See NREL/CP-5D00-73228 for preprint

NREL Publication Number

NREL/CP-5D00-74634

Keywords

distribution systems
dynamics
least-squares estimation
load parameters
voltage measurements

Access to Document

10.1109/ISIE.2019.8781530

Cite this

@conference{bd20e066e4ca4f97b45316eb5f4823c5,

title = "Online Static Load Model Estimation in Distribution Systems",

abstract = "This paper focuses on parameter identification for time-varying voltage-dependent polynomial load models in distribution systems - namely, the constant impedance (Z), constant current (I), and constant power (P). The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. The least-squares estimation method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations on the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system caused by varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data. Finally, the paper uses dynamic simulations data (synthetic high-resolution measurements) to further improve the estimation results.",

keywords = "distribution systems, dynamics, least-squares estimation, load parameters, voltage measurements",

author = "Venkat Krishnan and Yingchen Zhang and Hongda Ren and Noel Schulz",

note = "See NREL/CP-5D00-73228 for preprint; 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE) ; Conference date: 12-06-2019 Through 14-06-2019",

year = "2019",

doi = "10.1109/ISIE.2019.8781530",

language = "American English",

pages = "153--158",

}

TY - CONF

T1 - Online Static Load Model Estimation in Distribution Systems

AU - Krishnan, Venkat

AU - Zhang, Yingchen

AU - Ren, Hongda

AU - Schulz, Noel

N1 - See NREL/CP-5D00-73228 for preprint

PY - 2019

Y1 - 2019

N2 - This paper focuses on parameter identification for time-varying voltage-dependent polynomial load models in distribution systems - namely, the constant impedance (Z), constant current (I), and constant power (P). The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. The least-squares estimation method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations on the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system caused by varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data. Finally, the paper uses dynamic simulations data (synthetic high-resolution measurements) to further improve the estimation results.

AB - This paper focuses on parameter identification for time-varying voltage-dependent polynomial load models in distribution systems - namely, the constant impedance (Z), constant current (I), and constant power (P). The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. The least-squares estimation method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations on the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system caused by varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data. Finally, the paper uses dynamic simulations data (synthetic high-resolution measurements) to further improve the estimation results.

KW - distribution systems

KW - dynamics

KW - least-squares estimation

KW - load parameters

KW - voltage measurements

U2 - 10.1109/ISIE.2019.8781530

DO - 10.1109/ISIE.2019.8781530

M3 - Paper

SP - 153

EP - 158

T2 - 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)

Y2 - 12 June 2019 through 14 June 2019

ER -

Online Static Load Model Estimation in Distribution Systems

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

Access to Document

Fingerprint

Cite this