Experimental real-time testing of a decentralized PMU data-based power systems mode estimator

Ravi Shankar Singh; Hossein Hooshyar; Luigi Vanfretti

doi:10.1109/PESGM.2017.8274269

Experimental real-time testing of a decentralized PMU data-based power systems mode estimator

Ravi Shankar Singh, Hossein Hooshyar, Luigi Vanfretti

Electrical Energy Systems

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

Abstract

This paper presents the results and testing of a Phasor Measurement Unit (PMU) data-based mode estimation application deployed within a decentralized architecture using a real-time test platform. This work is a continuation of that in [1], which described a decentralized mode estimation architecture that enables the application to better detect local modes whose observability is affected by other more observable modes. The tests in this paper were carried out using an active distribution network (ADN) comprised of a high voltage network connected to a distribution grid including renewable energy resources (RES). The developed application was run in a decentralized architecture where each PMU was associated with its own processing unit which was running the application to estimate modes from the time-series data. The results of the decentralized mode estimation architecture are analyzed and compared with its centralized counterpart.

Original language	English
Title of host publication	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Place of Publication	Piscataway
Publisher	IEEE Computer Society
Number of pages	4
ISBN (Electronic)	9781538622124
DOIs	https://doi.org/10.1109/PESGM.2017.8274269
Publication status	Published - 29 Jan 2018
Event	2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, IL USA, Chicago, United States Duration: 16 Jul 2017 → 20 Jul 2017 http://www.pes-gm.org/2017 http://www.pes-gm.org/2017/

Conference

Conference	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Abbreviated title	PESGM 2017
Country	United States
City	Chicago
Period	16/07/17 → 20/07/17
Internet address	http://www.pes-gm.org/2017 http://www.pes-gm.org/2017/

Keywords

Decentralized Mode Estimation
Mode-meter
Oscillations
Phasor Measurement Unit (PMU)
Power System Monitoring

Access to Document

10.1109/PESGM.2017.8274269

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Cite this

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title = "Experimental real-time testing of a decentralized PMU data-based power systems mode estimator",

abstract = "This paper presents the results and testing of a Phasor Measurement Unit (PMU) data-based mode estimation application deployed within a decentralized architecture using a real-time test platform. This work is a continuation of that in [1], which described a decentralized mode estimation architecture that enables the application to better detect local modes whose observability is affected by other more observable modes. The tests in this paper were carried out using an active distribution network (ADN) comprised of a high voltage network connected to a distribution grid including renewable energy resources (RES). The developed application was run in a decentralized architecture where each PMU was associated with its own processing unit which was running the application to estimate modes from the time-series data. The results of the decentralized mode estimation architecture are analyzed and compared with its centralized counterpart.",

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author = "Singh, {Ravi Shankar} and Hossein Hooshyar and Luigi Vanfretti",

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note = "2017 IEEE Power and Energy Society General Meeting, PESGM 2017, PESGM 2017 ; Conference date: 16-07-2017 Through 20-07-2017",

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Singh, RS, Hooshyar, H & Vanfretti, L 2018, Experimental real-time testing of a decentralized PMU data-based power systems mode estimator. in 2017 IEEE Power and Energy Society General Meeting, PESGM 2017., 8274269, IEEE Computer Society, Piscataway, 2017 IEEE Power and Energy Society General Meeting, PESGM 2017, Chicago, United States, 16/07/17. https://doi.org/10.1109/PESGM.2017.8274269

Experimental real-time testing of a decentralized PMU data-based power systems mode estimator. / Singh, Ravi Shankar; Hooshyar, Hossein; Vanfretti, Luigi.

2017 IEEE Power and Energy Society General Meeting, PESGM 2017. Piscataway : IEEE Computer Society, 2018. 8274269.

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

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