Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements
The wide area situational awareness attempts at the expeditious detection of imminent system abnormalities and alerting system operators to take appropriate measures. Because the critical situation may arise in a system due to faults on transmission lines spanning over a long distance, phasor measur...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8905991/ |
| _version_ | 1818920761109250048 |
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| author | Kunja Bihari Swain Satya Sopan Mahato Murthy Cherukuri |
| author_facet | Kunja Bihari Swain Satya Sopan Mahato Murthy Cherukuri |
| author_sort | Kunja Bihari Swain |
| collection | DOAJ |
| description | The wide area situational awareness attempts at the expeditious detection of imminent system abnormalities and alerting system operators to take appropriate measures. Because the critical situation may arise in a system due to faults on transmission lines spanning over a long distance, phasor measurement units (PMUs) have become an indispensable measuring device to provide a dynamic view of such a wide area system. In this paper, the perception about a 200 km long transmission line has been achieved with the help of phasor measurements from PMU, which has the capability of reporting 200 phasors per second. The comprehension about the perceived event is accomplished by computing the deviations of current phasor magnitude as well as phase angles derived from synchronized phasor measurements using the phaselet algorithm. Based on the comprehension of the perceived event, a specific type of fault has been predicted using the Gaussian Naïve Bayes approach. In order to validate the proposed methodology, it has been implemented on a laboratory setup. |
| first_indexed | 2024-12-20T01:26:53Z |
| format | Article |
| id | doaj.art-de7ca494a14244b684a5e165f5c1f01b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T01:26:53Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-de7ca494a14244b684a5e165f5c1f01b2022-12-21T19:58:13ZengIEEEIEEE Access2169-35362019-01-01716818716820010.1109/ACCESS.2019.29543378905991Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor MeasurementsKunja Bihari Swain0https://orcid.org/0000-0001-5995-953XSatya Sopan Mahato1https://orcid.org/0000-0002-8019-4241Murthy Cherukuri2https://orcid.org/0000-0003-2958-5842Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Paralakhemundi, IndiaDepartment of Electronics and Communication Engineering, National Institute of Science and Technology, Berhampur, IndiaDepartment of Electrical and Electronics Engineering, National Institute of Science and Technology, Berhampur, IndiaThe wide area situational awareness attempts at the expeditious detection of imminent system abnormalities and alerting system operators to take appropriate measures. Because the critical situation may arise in a system due to faults on transmission lines spanning over a long distance, phasor measurement units (PMUs) have become an indispensable measuring device to provide a dynamic view of such a wide area system. In this paper, the perception about a 200 km long transmission line has been achieved with the help of phasor measurements from PMU, which has the capability of reporting 200 phasors per second. The comprehension about the perceived event is accomplished by computing the deviations of current phasor magnitude as well as phase angles derived from synchronized phasor measurements using the phaselet algorithm. Based on the comprehension of the perceived event, a specific type of fault has been predicted using the Gaussian Naïve Bayes approach. In order to validate the proposed methodology, it has been implemented on a laboratory setup.https://ieeexplore.ieee.org/document/8905991/Phasor measurement unitspower system protectionsituational awarenessphaseletGaussian Naïve Bayes |
| spellingShingle | Kunja Bihari Swain Satya Sopan Mahato Murthy Cherukuri Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements IEEE Access Phasor measurement units power system protection situational awareness phaselet Gaussian Naïve Bayes |
| title | Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements |
| title_full | Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements |
| title_fullStr | Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements |
| title_full_unstemmed | Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements |
| title_short | Expeditious Situational Awareness-Based Transmission Line Fault Classification and Prediction Using Synchronized Phasor Measurements |
| title_sort | expeditious situational awareness based transmission line fault classification and prediction using synchronized phasor measurements |
| topic | Phasor measurement units power system protection situational awareness phaselet Gaussian Naïve Bayes |
| url | https://ieeexplore.ieee.org/document/8905991/ |
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