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The computation of confidence intervals for the state parameters of power systems

Background: In the past few decades, a significant volume of work has been carried out on various aspects of the state estimation problem to estimate an optimum state vector of the power system. This problem has been focused on, in previous studies regarding the computational efficiency and numerica...

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Main Authors: Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.
Format: Article
Published: SpringerOpen 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994709553&doi=10.1186%2fs40064-016-3631-1&partnerID=40&md5=7fa9c40371e29239d8f576fcb6a10914
http://eprints.utp.edu.my/31027/
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spelling my.utp.eprints.310272022-03-25T07:53:39Z The computation of confidence intervals for the state parameters of power systems Khan, Z. Razali, R.B. Daud, H. Nor, N.M. Fotuhi-Firuzabad, M. Krebs, K.L. Background: In the past few decades, a significant volume of work has been carried out on various aspects of the state estimation problem to estimate an optimum state vector of the power system. This problem has been focused on, in previous studies regarding the computational efficiency and numerical robustness in view to find point estimates for system state parameters. This current investigation, constructed confidence intervals for the unknown state parameters of the system. The research indicates that confidence intervals can yield addition useful information about the estimated parameters. Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. The statistical assumptions of the measurement errors have been utilized to characterize the probabilistic behavior of the estimated parameters in terms of confidence intervals. The Gauss�Newton algorithm has been adopted for maximizing the likelihood function of the processing measurements and obtaining the confidence intervals. Results: The usage of the confidence intervals was demonstrated through Monte Carlo experiments on a real dataset of the 6-bus and IEEE 14-bus power systems for both small and large sample sizes. The confidence intervals were constructed for the test networks for the sample of measurements 18, 28, 44 and 68 based on the redundancy ratio R. The proposed interval estimates outperformed for the sample sizes of 28 in the 6 bus and 68 in the IEEE 14-bus systems, respectively. The poor performance for the constructed interval estimates have been reported even for the large sample sizes in the existence of contaminated measurements. Conclusions: The results of the study show that the method is effective and practically applicable in the state estimation of a power system. The constructed confidence intervals for the system state parameters adequately perform for the lager sample size. However, the existence of the gross errors in the processing measurements had severe effect on the performance of the proposed interval estimates. © 2016, The Author(s). SpringerOpen 2016 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994709553&doi=10.1186%2fs40064-016-3631-1&partnerID=40&md5=7fa9c40371e29239d8f576fcb6a10914 Khan, Z. and Razali, R.B. and Daud, H. and Nor, N.M. and Fotuhi-Firuzabad, M. and Krebs, K.L. (2016) The computation of confidence intervals for the state parameters of power systems. SpringerPlus, 5 (1). http://eprints.utp.edu.my/31027/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Background: In the past few decades, a significant volume of work has been carried out on various aspects of the state estimation problem to estimate an optimum state vector of the power system. This problem has been focused on, in previous studies regarding the computational efficiency and numerical robustness in view to find point estimates for system state parameters. This current investigation, constructed confidence intervals for the unknown state parameters of the system. The research indicates that confidence intervals can yield addition useful information about the estimated parameters. Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. The statistical assumptions of the measurement errors have been utilized to characterize the probabilistic behavior of the estimated parameters in terms of confidence intervals. The Gauss�Newton algorithm has been adopted for maximizing the likelihood function of the processing measurements and obtaining the confidence intervals. Results: The usage of the confidence intervals was demonstrated through Monte Carlo experiments on a real dataset of the 6-bus and IEEE 14-bus power systems for both small and large sample sizes. The confidence intervals were constructed for the test networks for the sample of measurements 18, 28, 44 and 68 based on the redundancy ratio R. The proposed interval estimates outperformed for the sample sizes of 28 in the 6 bus and 68 in the IEEE 14-bus systems, respectively. The poor performance for the constructed interval estimates have been reported even for the large sample sizes in the existence of contaminated measurements. Conclusions: The results of the study show that the method is effective and practically applicable in the state estimation of a power system. The constructed confidence intervals for the system state parameters adequately perform for the lager sample size. However, the existence of the gross errors in the processing measurements had severe effect on the performance of the proposed interval estimates. © 2016, The Author(s).
format Article
author Khan, Z.
Razali, R.B.
Daud, H.
Nor, N.M.
Fotuhi-Firuzabad, M.
Krebs, K.L.
spellingShingle Khan, Z.
Razali, R.B.
Daud, H.
Nor, N.M.
Fotuhi-Firuzabad, M.
Krebs, K.L.
The computation of confidence intervals for the state parameters of power systems
author_facet Khan, Z.
Razali, R.B.
Daud, H.
Nor, N.M.
Fotuhi-Firuzabad, M.
Krebs, K.L.
author_sort Khan, Z.
title The computation of confidence intervals for the state parameters of power systems
title_short The computation of confidence intervals for the state parameters of power systems
title_full The computation of confidence intervals for the state parameters of power systems
title_fullStr The computation of confidence intervals for the state parameters of power systems
title_full_unstemmed The computation of confidence intervals for the state parameters of power systems
title_sort computation of confidence intervals for the state parameters of power systems
publisher SpringerOpen
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994709553&doi=10.1186%2fs40064-016-3631-1&partnerID=40&md5=7fa9c40371e29239d8f576fcb6a10914
http://eprints.utp.edu.my/31027/
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score 13.211869

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