Experimental measurement of PMU error distribution and its impact on load model identification

Xinran Zhang; Chao Lu; Junjie Lin; Ying Wang; Jifeng Wang; He Huang; Yinsheng Su

doi:10.1109/PESGM.2016.7741069

Experimental measurement of PMU error distribution and its impact on load model identification

Xinran Zhang
, Chao Lu
, Junjie Lin
, Ying Wang
, Jifeng Wang
, He Huang
, Yinsheng Su

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

20 Scopus citations

Abstract

Recently, many aspects of power system dynamic analysis, including oscillation identification, load model identification and system state estimation, are conducted based on the measurement data from phasor measurement unit (PMU). However, the impact of PMU measurement error, especially in power system dynamic process, has an assignable impact on these analysis results and thus cannot be neglected. In this paper, the requirements from IEEE standards and the analyze method for PMU measurement error are proposed first. Then, the ambient signal based identification method and the impact of measurement error for dynamic load model parameters is introduced. Afterwards, the stochastic distribution and frequency spectrum of PMU measurement error are measured through an experiment carried in a power system hardware simulation platform. Finally, the impact of PMU measurement error on the identification results of load model is simulated in WSCC 9 bus system.

Original language	English
Title of host publication	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Publisher	IEEE Computer Society
ISBN (Electronic)	9781509041688
DOIs	https://doi.org/10.1109/PESGM.2016.7741069
State	Published - 10 Nov 2016
Externally published	Yes
Event	2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States Duration: 17 Jul 2016 → 21 Jul 2016

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2016-November
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Country/Territory	United States
City	Boston
Period	17/07/16 → 21/07/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Ambient signal
Load model identification
PMU measurement error
Simulation experiment platform

Access to Document

10.1109/PESGM.2016.7741069

Cite this

Zhang, X., Lu, C., Lin, J., Wang, Y., Wang, J., Huang, H., & Su, Y. (2016). Experimental measurement of PMU error distribution and its impact on load model identification. In 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 Article 7741069 (IEEE Power and Energy Society General Meeting; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/PESGM.2016.7741069

@inproceedings{820b9161e80a481ea97ee8acf1e25a2b,

title = "Experimental measurement of PMU error distribution and its impact on load model identification",

abstract = "Recently, many aspects of power system dynamic analysis, including oscillation identification, load model identification and system state estimation, are conducted based on the measurement data from phasor measurement unit (PMU). However, the impact of PMU measurement error, especially in power system dynamic process, has an assignable impact on these analysis results and thus cannot be neglected. In this paper, the requirements from IEEE standards and the analyze method for PMU measurement error are proposed first. Then, the ambient signal based identification method and the impact of measurement error for dynamic load model parameters is introduced. Afterwards, the stochastic distribution and frequency spectrum of PMU measurement error are measured through an experiment carried in a power system hardware simulation platform. Finally, the impact of PMU measurement error on the identification results of load model is simulated in WSCC 9 bus system.",

keywords = "Ambient signal, Load model identification, PMU measurement error, Simulation experiment platform",

author = "Xinran Zhang and Chao Lu and Junjie Lin and Ying Wang and Jifeng Wang and He Huang and Yinsheng Su",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 ; Conference date: 17-07-2016 Through 21-07-2016",

year = "2016",

month = nov,

day = "10",

doi = "10.1109/PESGM.2016.7741069",

language = "英语",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2016 IEEE Power and Energy Society General Meeting, PESGM 2016",

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Zhang, X, Lu, C, Lin, J, Wang, Y, Wang, J, Huang, H & Su, Y 2016, Experimental measurement of PMU error distribution and its impact on load model identification. in 2016 IEEE Power and Energy Society General Meeting, PESGM 2016., 7741069, IEEE Power and Energy Society General Meeting, vol. 2016-November, IEEE Computer Society, 2016 IEEE Power and Energy Society General Meeting, PESGM 2016, Boston, United States, 17/07/16. https://doi.org/10.1109/PESGM.2016.7741069

Experimental measurement of PMU error distribution and its impact on load model identification. / Zhang, Xinran; Lu, Chao; Lin, Junjie et al.
2016 IEEE Power and Energy Society General Meeting, PESGM 2016. IEEE Computer Society, 2016. 7741069 (IEEE Power and Energy Society General Meeting; Vol. 2016-November).

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

TY - GEN

T1 - Experimental measurement of PMU error distribution and its impact on load model identification

AU - Zhang, Xinran

AU - Lu, Chao

AU - Lin, Junjie

AU - Wang, Ying

AU - Wang, Jifeng

AU - Huang, He

AU - Su, Yinsheng

PY - 2016/11/10

Y1 - 2016/11/10

N2 - Recently, many aspects of power system dynamic analysis, including oscillation identification, load model identification and system state estimation, are conducted based on the measurement data from phasor measurement unit (PMU). However, the impact of PMU measurement error, especially in power system dynamic process, has an assignable impact on these analysis results and thus cannot be neglected. In this paper, the requirements from IEEE standards and the analyze method for PMU measurement error are proposed first. Then, the ambient signal based identification method and the impact of measurement error for dynamic load model parameters is introduced. Afterwards, the stochastic distribution and frequency spectrum of PMU measurement error are measured through an experiment carried in a power system hardware simulation platform. Finally, the impact of PMU measurement error on the identification results of load model is simulated in WSCC 9 bus system.

AB - Recently, many aspects of power system dynamic analysis, including oscillation identification, load model identification and system state estimation, are conducted based on the measurement data from phasor measurement unit (PMU). However, the impact of PMU measurement error, especially in power system dynamic process, has an assignable impact on these analysis results and thus cannot be neglected. In this paper, the requirements from IEEE standards and the analyze method for PMU measurement error are proposed first. Then, the ambient signal based identification method and the impact of measurement error for dynamic load model parameters is introduced. Afterwards, the stochastic distribution and frequency spectrum of PMU measurement error are measured through an experiment carried in a power system hardware simulation platform. Finally, the impact of PMU measurement error on the identification results of load model is simulated in WSCC 9 bus system.

KW - Ambient signal

KW - Load model identification

KW - PMU measurement error

KW - Simulation experiment platform

UR - https://www.scopus.com/pages/publications/85002342335

U2 - 10.1109/PESGM.2016.7741069

DO - 10.1109/PESGM.2016.7741069

M3 - 会议稿件

AN - SCOPUS:85002342335

T3 - IEEE Power and Energy Society General Meeting

BT - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

PB - IEEE Computer Society

T2 - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

Y2 - 17 July 2016 through 21 July 2016

ER -

Experimental measurement of PMU error distribution and its impact on load model identification

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UN SDGs

Keywords

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