PMU-Based event localization technique for wide-area power system

Do In Kim, Austin White, Yong June Shin

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This paper presents an online event location estimating process in a wide-area power system using the phasor measurement unit (PMU). For real-world applications of PMU-based event location estimation (ELE), it is necessary to consider the insufficiency of PMU data caused by a lack of PMUs, communication failure, PMU malfunction, etc., because insufficient PMU data cannot guarantee event observability over the entire network. To ensure possible event locations in a real-world system, an estimation method is developed by combining offline zonal analysis and an online ELE algorithm. The K-mean clustering method is utilized for electrical-bus clustering, which enables us to recognize separate electrical zones (EZs). Then, we propose a two-stage ELE algorithm by estimating the event EZ and localizing the specified event section within the estimated EZ. Proposed ELE algorithm is applied to a real-world PMU data collected from southwestern part of the United States. Finally, successful results from a real-world PMU data application are presented at the end of this paper.

Original languageEnglish
Article number8334283
Pages (from-to)5875-5883
Number of pages9
JournalIEEE Transactions on Power Systems
Volume33
Issue number6
DOIs
Publication statusPublished - 2018 Nov

Fingerprint

Phasor measurement units
Observability
Communication

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

@article{5f37f06fdde84443b365d7e94268d2c8,
title = "PMU-Based event localization technique for wide-area power system",
abstract = "This paper presents an online event location estimating process in a wide-area power system using the phasor measurement unit (PMU). For real-world applications of PMU-based event location estimation (ELE), it is necessary to consider the insufficiency of PMU data caused by a lack of PMUs, communication failure, PMU malfunction, etc., because insufficient PMU data cannot guarantee event observability over the entire network. To ensure possible event locations in a real-world system, an estimation method is developed by combining offline zonal analysis and an online ELE algorithm. The K-mean clustering method is utilized for electrical-bus clustering, which enables us to recognize separate electrical zones (EZs). Then, we propose a two-stage ELE algorithm by estimating the event EZ and localizing the specified event section within the estimated EZ. Proposed ELE algorithm is applied to a real-world PMU data collected from southwestern part of the United States. Finally, successful results from a real-world PMU data application are presented at the end of this paper.",
author = "Kim, {Do In} and Austin White and Shin, {Yong June}",
year = "2018",
month = "11",
doi = "10.1109/TPWRS.2018.2824851",
language = "English",
volume = "33",
pages = "5875--5883",
journal = "IEEE Transactions on Power Systems",
issn = "0885-8950",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "6",

}

PMU-Based event localization technique for wide-area power system. / Kim, Do In; White, Austin; Shin, Yong June.

In: IEEE Transactions on Power Systems, Vol. 33, No. 6, 8334283, 11.2018, p. 5875-5883.

Research output: Contribution to journalArticle

TY - JOUR

T1 - PMU-Based event localization technique for wide-area power system

AU - Kim, Do In

AU - White, Austin

AU - Shin, Yong June

PY - 2018/11

Y1 - 2018/11

N2 - This paper presents an online event location estimating process in a wide-area power system using the phasor measurement unit (PMU). For real-world applications of PMU-based event location estimation (ELE), it is necessary to consider the insufficiency of PMU data caused by a lack of PMUs, communication failure, PMU malfunction, etc., because insufficient PMU data cannot guarantee event observability over the entire network. To ensure possible event locations in a real-world system, an estimation method is developed by combining offline zonal analysis and an online ELE algorithm. The K-mean clustering method is utilized for electrical-bus clustering, which enables us to recognize separate electrical zones (EZs). Then, we propose a two-stage ELE algorithm by estimating the event EZ and localizing the specified event section within the estimated EZ. Proposed ELE algorithm is applied to a real-world PMU data collected from southwestern part of the United States. Finally, successful results from a real-world PMU data application are presented at the end of this paper.

AB - This paper presents an online event location estimating process in a wide-area power system using the phasor measurement unit (PMU). For real-world applications of PMU-based event location estimation (ELE), it is necessary to consider the insufficiency of PMU data caused by a lack of PMUs, communication failure, PMU malfunction, etc., because insufficient PMU data cannot guarantee event observability over the entire network. To ensure possible event locations in a real-world system, an estimation method is developed by combining offline zonal analysis and an online ELE algorithm. The K-mean clustering method is utilized for electrical-bus clustering, which enables us to recognize separate electrical zones (EZs). Then, we propose a two-stage ELE algorithm by estimating the event EZ and localizing the specified event section within the estimated EZ. Proposed ELE algorithm is applied to a real-world PMU data collected from southwestern part of the United States. Finally, successful results from a real-world PMU data application are presented at the end of this paper.

UR - http://www.scopus.com/inward/record.url?scp=85045180211&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85045180211&partnerID=8YFLogxK

U2 - 10.1109/TPWRS.2018.2824851

DO - 10.1109/TPWRS.2018.2824851

M3 - Article

AN - SCOPUS:85045180211

VL - 33

SP - 5875

EP - 5883

JO - IEEE Transactions on Power Systems

JF - IEEE Transactions on Power Systems

SN - 0885-8950

IS - 6

M1 - 8334283

ER -