Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation

Hesam Khazraj; Filipe Miguel Faria da Silva; Claus Leth Bak; Udaya  Annakkage

doi:10.1109/UPEC.2017.8231940

Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation

Hesam Khazraj, Filipe Miguel Faria da Silva, Claus Leth Bak, Udaya Annakkage

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

4 Citations (Scopus)

Abstract

Detection and analysis of bad data is an important sector of the static state estimation. This paper addresses single and multiple bad data in the modern phasor measurement unit (PMU)-based power system static state estimations. To accomplish this objective, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the state estimation. The proposed algorithms of phasor measurements utilization in state estimation can detect and identify single and multiple bad data in redundant and critical measurements. To validate simulations, IEEE 30 bus system are implemented in PowerFactory and Matlab is used to solve proposed state estimation using postprocessing of PMUs and mixed methods. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analyze of bad data are available by the result of largest normalized residual test.

Original language	English
Title of host publication	Proceedings of 2017 52nd International Universities Power Engineering Conference (UPEC 2017)
Number of pages	6
Publisher	IEEE Press
Publication date	Aug 2017
ISBN (Electronic)	978-1-5386-2344-2
DOIs	https://doi.org/10.1109/UPEC.2017.8231940
Publication status	Published - Aug 2017
Event	2017 52nd International Universities Power Engineering Conference (UPEC) - Heraklion, Greece Duration: 28 Aug 2017 → 31 Aug 2017

Conference

Conference	2017 52nd International Universities Power Engineering Conference (UPEC)
Country/Territory	Greece
City	Heraklion
Period	28/08/2017 → 31/08/2017

Keywords

Bad Data
Critical Measurement
Largest Normalized Residual
Phase Measurement unit
State Estimation

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@inproceedings{75bb0229f6a146f08900ef91300b9c96,

title = "Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation",

abstract = "Detection and analysis of bad data is an important sector of the static state estimation. This paper addresses single and multiple bad data in the modern phasor measurement unit (PMU)-based power system static state estimations. To accomplish this objective, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the state estimation. The proposed algorithms of phasor measurements utilization in state estimation can detect and identify single and multiple bad data in redundant and critical measurements. To validate simulations, IEEE 30 bus system are implemented in PowerFactory and Matlab is used to solve proposed state estimation using postprocessing of PMUs and mixed methods. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analyze of bad data are available by the result of largest normalized residual test.",

keywords = "Bad Data, Critical Measurement, Largest Normalized Residual, Phase Measurement unit, State Estimation",

author = "Hesam Khazraj and Silva, {Filipe Miguel Faria da} and Bak, {Claus Leth} and Udaya Annakkage",

year = "2017",

month = aug,

doi = "10.1109/UPEC.2017.8231940",

language = "English",

booktitle = "Proceedings of 2017 52nd International Universities Power Engineering Conference (UPEC 2017)",

publisher = "IEEE Press",

note = "2017 52nd International Universities Power Engineering Conference (UPEC) ; Conference date: 28-08-2017 Through 31-08-2017",

}

Khazraj, H, Silva, FMFD , Bak, CL & Annakkage, U 2017, Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation. in Proceedings of 2017 52nd International Universities Power Engineering Conference (UPEC 2017). IEEE Press, 2017 52nd International Universities Power Engineering Conference (UPEC), Heraklion, Greece, 28/08/2017. https://doi.org/10.1109/UPEC.2017.8231940

Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation. / Khazraj, Hesam; Silva, Filipe Miguel Faria da ; Bak, Claus Leth et al.
Proceedings of 2017 52nd International Universities Power Engineering Conference (UPEC 2017). IEEE Press, 2017.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

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AU - Silva, Filipe Miguel Faria da

AU - Bak, Claus Leth

AU - Annakkage, Udaya

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N2 - Detection and analysis of bad data is an important sector of the static state estimation. This paper addresses single and multiple bad data in the modern phasor measurement unit (PMU)-based power system static state estimations. To accomplish this objective, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the state estimation. The proposed algorithms of phasor measurements utilization in state estimation can detect and identify single and multiple bad data in redundant and critical measurements. To validate simulations, IEEE 30 bus system are implemented in PowerFactory and Matlab is used to solve proposed state estimation using postprocessing of PMUs and mixed methods. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analyze of bad data are available by the result of largest normalized residual test.

AB - Detection and analysis of bad data is an important sector of the static state estimation. This paper addresses single and multiple bad data in the modern phasor measurement unit (PMU)-based power system static state estimations. To accomplish this objective, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the state estimation. The proposed algorithms of phasor measurements utilization in state estimation can detect and identify single and multiple bad data in redundant and critical measurements. To validate simulations, IEEE 30 bus system are implemented in PowerFactory and Matlab is used to solve proposed state estimation using postprocessing of PMUs and mixed methods. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analyze of bad data are available by the result of largest normalized residual test.

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KW - Largest Normalized Residual

KW - Phase Measurement unit

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DO - 10.1109/UPEC.2017.8231940

M3 - Article in proceeding

BT - Proceedings of 2017 52nd International Universities Power Engineering Conference (UPEC 2017)

PB - IEEE Press

T2 - 2017 52nd International Universities Power Engineering Conference (UPEC)

Y2 - 28 August 2017 through 31 August 2017

ER -

Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation

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Keywords

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