Signal-dependent preprocessing of buffered PMU measurements for hybrid state estimation

Neelabh Kashyap; Stefan Werner; Jarmo Lunden

doi:10.1109/I2MTC.2016.7520340

Signal-dependent preprocessing of buffered PMU measurements for hybrid state estimation

Neelabh Kashyap, Stefan Werner, Jarmo Lunden

Department of Signal Processing and Acoustics

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

2 Citations (Scopus)

Abstract

This paper presents a signal-dependent scheme for selecting the length of the averaging window for PMU measurements to improve the performance of the power system state estimator. The method is based on the Shewhart method for detecting mean shifts in the buffered data. We suggest ways to tune the parameters of the scheme by deriving expressions for the probability of false alarm and the probability of using the entire buffer given all buffered data have the same mean. We also propose a method to handle oscillatory transients captured by the buffered PMU measurements, which may otherwise degrade the performance of the buffering scheme. Simulations performed on the IEEE 14-bus test system show that the proposed method outperforms an existing state-of-the-art method.

Original language	English
Title of host publication	Instrumentation and Measurement Technology Conference Proceedings (I2MTC), 2016 IEEE International
Publisher	IEEE
Number of pages	6
Volume	2016-July
ISBN (Electronic)	978-1-4673-9220-4
ISBN (Print)	978-1-4673-9221-1
DOIs	https://doi.org/10.1109/I2MTC.2016.7520340
Publication status	Published - 22 Jul 2016
MoE publication type	A4 Article in a conference publication
Event	IEEE International Instrumentation and Measurement Technology Conference - Taipei, Taiwan, Republic of China Duration: 23 May 2016 → 26 May 2016 Conference number: 12

Conference

Conference	IEEE International Instrumentation and Measurement Technology Conference
Abbreviated title	MTC
Country/Territory	Taiwan, Republic of China
City	Taipei
Period	23/05/2016 → 26/05/2016

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10.1109/I2MTC.2016.7520340

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title = "Signal-dependent preprocessing of buffered PMU measurements for hybrid state estimation",

abstract = "This paper presents a signal-dependent scheme for selecting the length of the averaging window for PMU measurements to improve the performance of the power system state estimator. The method is based on the Shewhart method for detecting mean shifts in the buffered data. We suggest ways to tune the parameters of the scheme by deriving expressions for the probability of false alarm and the probability of using the entire buffer given all buffered data have the same mean. We also propose a method to handle oscillatory transients captured by the buffered PMU measurements, which may otherwise degrade the performance of the buffering scheme. Simulations performed on the IEEE 14-bus test system show that the proposed method outperforms an existing state-of-the-art method.",

author = "Neelabh Kashyap and Stefan Werner and Jarmo Lunden",

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Kashyap, N, Werner, S & Lunden, J 2016, Signal-dependent preprocessing of buffered PMU measurements for hybrid state estimation. in Instrumentation and Measurement Technology Conference Proceedings (I2MTC), 2016 IEEE International. vol. 2016-July, 7520340, IEEE, IEEE International Instrumentation and Measurement Technology Conference, Taipei, Taiwan, Republic of China, 23/05/2016. https://doi.org/10.1109/I2MTC.2016.7520340

Signal-dependent preprocessing of buffered PMU measurements for hybrid state estimation. / Kashyap, Neelabh; Werner, Stefan; Lunden, Jarmo.

Instrumentation and Measurement Technology Conference Proceedings (I2MTC), 2016 IEEE International. Vol. 2016-July IEEE, 2016. 7520340.

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

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N2 - This paper presents a signal-dependent scheme for selecting the length of the averaging window for PMU measurements to improve the performance of the power system state estimator. The method is based on the Shewhart method for detecting mean shifts in the buffered data. We suggest ways to tune the parameters of the scheme by deriving expressions for the probability of false alarm and the probability of using the entire buffer given all buffered data have the same mean. We also propose a method to handle oscillatory transients captured by the buffered PMU measurements, which may otherwise degrade the performance of the buffering scheme. Simulations performed on the IEEE 14-bus test system show that the proposed method outperforms an existing state-of-the-art method.

AB - This paper presents a signal-dependent scheme for selecting the length of the averaging window for PMU measurements to improve the performance of the power system state estimator. The method is based on the Shewhart method for detecting mean shifts in the buffered data. We suggest ways to tune the parameters of the scheme by deriving expressions for the probability of false alarm and the probability of using the entire buffer given all buffered data have the same mean. We also propose a method to handle oscillatory transients captured by the buffered PMU measurements, which may otherwise degrade the performance of the buffering scheme. Simulations performed on the IEEE 14-bus test system show that the proposed method outperforms an existing state-of-the-art method.

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PB - IEEE

T2 - IEEE International Instrumentation and Measurement Technology Conference

Y2 - 23 May 2016 through 26 May 2016

ER -

Signal-dependent preprocessing of buffered PMU measurements for hybrid state estimation

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