State estimation with sampling offsets in wide area measurement systems

Hoi To Wai, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

An implicit assumption made in studies on state estimation is that the time and frequency at which these measurements are taken is consistent across all the distributed sensing sites. For instance, in the literatures on Wide Area Measurement Systems (WAMS) deployed in the power grid, where the sensors equipped with Global Positioning Signals (GPS), the sensing sites are deemed capable to provide perfectly synchronous readings at the various sampling sites. The validity of the assumption may need to be re-examined with the recent advancements in decentralized state estimation algorithms. Importantly, when there are timing offsets between sampling devices, the effects on the measurement system's performance can be catastrophic. The prevalent point of view is to either study the resulting error, or to resort to Kalman filtering for aligning the measurements. Taking on this view typically requires additional information about the underlying state. In this paper, we revisit the problem of state estimation and propose a new model for data acquisition under asynchronous sampling. The key idea is to apply sampling theory and to exploit the redundancy in the spatial sampling to interpolate the system state. We provide a necessary and sufficient condition for identifiability of the time offsets and propose an algorithm for the joint regression on state and timing offsets. The efficacy of the proposed algorithm is shown by numerical simulations.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
PublisherIEEE Computer Society
Pages49-52
Number of pages4
ISBN (Print)9781479914814
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 - A Coruna, Spain
Duration: Jun 22 2014Jun 25 2014

Other

Other2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
CountrySpain
CityA Coruna
Period6/22/146/25/14

Fingerprint

Electric power system measurement
State estimation
Sampling
Redundancy
Data acquisition
Sensors
Computer simulation

Keywords

  • sampling offsets
  • Smart grid
  • state estimation

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Wai, H. T., & Scaglione, A. (2014). State estimation with sampling offsets in wide area measurement systems. In Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (pp. 49-52). [6882335] IEEE Computer Society. https://doi.org/10.1109/SAM.2014.6882335

State estimation with sampling offsets in wide area measurement systems. / Wai, Hoi To; Scaglione, Anna.

Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. IEEE Computer Society, 2014. p. 49-52 6882335.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wai, HT & Scaglione, A 2014, State estimation with sampling offsets in wide area measurement systems. in Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop., 6882335, IEEE Computer Society, pp. 49-52, 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014, A Coruna, Spain, 6/22/14. https://doi.org/10.1109/SAM.2014.6882335
Wai HT, Scaglione A. State estimation with sampling offsets in wide area measurement systems. In Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. IEEE Computer Society. 2014. p. 49-52. 6882335 https://doi.org/10.1109/SAM.2014.6882335
Wai, Hoi To ; Scaglione, Anna. / State estimation with sampling offsets in wide area measurement systems. Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. IEEE Computer Society, 2014. pp. 49-52
@inproceedings{a5b22eaee4d14ae6b910b4692a0901d1,
title = "State estimation with sampling offsets in wide area measurement systems",
abstract = "An implicit assumption made in studies on state estimation is that the time and frequency at which these measurements are taken is consistent across all the distributed sensing sites. For instance, in the literatures on Wide Area Measurement Systems (WAMS) deployed in the power grid, where the sensors equipped with Global Positioning Signals (GPS), the sensing sites are deemed capable to provide perfectly synchronous readings at the various sampling sites. The validity of the assumption may need to be re-examined with the recent advancements in decentralized state estimation algorithms. Importantly, when there are timing offsets between sampling devices, the effects on the measurement system's performance can be catastrophic. The prevalent point of view is to either study the resulting error, or to resort to Kalman filtering for aligning the measurements. Taking on this view typically requires additional information about the underlying state. In this paper, we revisit the problem of state estimation and propose a new model for data acquisition under asynchronous sampling. The key idea is to apply sampling theory and to exploit the redundancy in the spatial sampling to interpolate the system state. We provide a necessary and sufficient condition for identifiability of the time offsets and propose an algorithm for the joint regression on state and timing offsets. The efficacy of the proposed algorithm is shown by numerical simulations.",
keywords = "sampling offsets, Smart grid, state estimation",
author = "Wai, {Hoi To} and Anna Scaglione",
year = "2014",
doi = "10.1109/SAM.2014.6882335",
language = "English (US)",
isbn = "9781479914814",
pages = "49--52",
booktitle = "Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop",
publisher = "IEEE Computer Society",

}

TY - GEN

T1 - State estimation with sampling offsets in wide area measurement systems

AU - Wai, Hoi To

AU - Scaglione, Anna

PY - 2014

Y1 - 2014

N2 - An implicit assumption made in studies on state estimation is that the time and frequency at which these measurements are taken is consistent across all the distributed sensing sites. For instance, in the literatures on Wide Area Measurement Systems (WAMS) deployed in the power grid, where the sensors equipped with Global Positioning Signals (GPS), the sensing sites are deemed capable to provide perfectly synchronous readings at the various sampling sites. The validity of the assumption may need to be re-examined with the recent advancements in decentralized state estimation algorithms. Importantly, when there are timing offsets between sampling devices, the effects on the measurement system's performance can be catastrophic. The prevalent point of view is to either study the resulting error, or to resort to Kalman filtering for aligning the measurements. Taking on this view typically requires additional information about the underlying state. In this paper, we revisit the problem of state estimation and propose a new model for data acquisition under asynchronous sampling. The key idea is to apply sampling theory and to exploit the redundancy in the spatial sampling to interpolate the system state. We provide a necessary and sufficient condition for identifiability of the time offsets and propose an algorithm for the joint regression on state and timing offsets. The efficacy of the proposed algorithm is shown by numerical simulations.

AB - An implicit assumption made in studies on state estimation is that the time and frequency at which these measurements are taken is consistent across all the distributed sensing sites. For instance, in the literatures on Wide Area Measurement Systems (WAMS) deployed in the power grid, where the sensors equipped with Global Positioning Signals (GPS), the sensing sites are deemed capable to provide perfectly synchronous readings at the various sampling sites. The validity of the assumption may need to be re-examined with the recent advancements in decentralized state estimation algorithms. Importantly, when there are timing offsets between sampling devices, the effects on the measurement system's performance can be catastrophic. The prevalent point of view is to either study the resulting error, or to resort to Kalman filtering for aligning the measurements. Taking on this view typically requires additional information about the underlying state. In this paper, we revisit the problem of state estimation and propose a new model for data acquisition under asynchronous sampling. The key idea is to apply sampling theory and to exploit the redundancy in the spatial sampling to interpolate the system state. We provide a necessary and sufficient condition for identifiability of the time offsets and propose an algorithm for the joint regression on state and timing offsets. The efficacy of the proposed algorithm is shown by numerical simulations.

KW - sampling offsets

KW - Smart grid

KW - state estimation

UR - http://www.scopus.com/inward/record.url?scp=84907418664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84907418664&partnerID=8YFLogxK

U2 - 10.1109/SAM.2014.6882335

DO - 10.1109/SAM.2014.6882335

M3 - Conference contribution

SN - 9781479914814

SP - 49

EP - 52

BT - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop

PB - IEEE Computer Society

ER -