A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems
Synchrophasor based applications become more and more popular in today’s control centers to monitor and control transient system events. This can ensure secure system operation when dealing with bidirectional power flows, diminishing reserves and an increased number of active grid components. Today’...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/15/5209 |
| _version_ | 1797561052402024448 |
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| author | Andre Kummerow Cristian Monsalve Christoph Brosinsky Steffen Nicolai Dirk Westermann |
| author_facet | Andre Kummerow Cristian Monsalve Christoph Brosinsky Steffen Nicolai Dirk Westermann |
| author_sort | Andre Kummerow |
| collection | DOAJ |
| description | Synchrophasor based applications become more and more popular in today’s control centers to monitor and control transient system events. This can ensure secure system operation when dealing with bidirectional power flows, diminishing reserves and an increased number of active grid components. Today’s synchrophasor applications provide a lot of additional information about the dynamic system behavior but without significant improvement of the system operation due to the lack of interpretable and condensed results as well as missing integration into existing decision-making processes. This study presents a holistic framework for novel machine learning based applications analyzing both historical as well as online synchrophasor data streams. Different methods from dimension reduction, anomaly detection as well as time series classification are used to automatically detect disturbances combined with a web-based online visualization tool. This enables automated decision-making processes in control centers to mitigate critical system states and to ensure secure system operations (e.g., by activating curate actions). Measurement and simulation-based results are presented to evaluate the proposed synchrophasor application modules for different use cases at the transmission and distribution level. |
| first_indexed | 2024-03-10T18:08:52Z |
| format | Article |
| id | doaj.art-36cd8993f8924838b8e867a05b37eba9 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T18:08:52Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-36cd8993f8924838b8e867a05b37eba92023-11-20T08:16:41ZengMDPI AGApplied Sciences2076-34172020-07-011015520910.3390/app10155209A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power SystemsAndre Kummerow0Cristian Monsalve1Christoph Brosinsky2Steffen Nicolai3Dirk Westermann4Department of Energy, Fraunhofer IOSB, IOSB-AST Ilmenau, Fraunhofer Institute for Optronics, System Technologies and Image Exploitation, Am Vogelherd 90, 98693 Ilmenau, GermanyDepartment of Energy, Fraunhofer IOSB, IOSB-AST Ilmenau, Fraunhofer Institute for Optronics, System Technologies and Image Exploitation, Am Vogelherd 90, 98693 Ilmenau, GermanyInstitute for Electrical Energy and Control Technology, Technische Universität Ilmenau, Gustav-Kirchhoff-Strasse 1, 98693 Ilmenau, GermanyDepartment of Energy, Fraunhofer IOSB, IOSB-AST Ilmenau, Fraunhofer Institute for Optronics, System Technologies and Image Exploitation, Am Vogelherd 90, 98693 Ilmenau, GermanyInstitute for Electrical Energy and Control Technology, Technische Universität Ilmenau, Gustav-Kirchhoff-Strasse 1, 98693 Ilmenau, GermanySynchrophasor based applications become more and more popular in today’s control centers to monitor and control transient system events. This can ensure secure system operation when dealing with bidirectional power flows, diminishing reserves and an increased number of active grid components. Today’s synchrophasor applications provide a lot of additional information about the dynamic system behavior but without significant improvement of the system operation due to the lack of interpretable and condensed results as well as missing integration into existing decision-making processes. This study presents a holistic framework for novel machine learning based applications analyzing both historical as well as online synchrophasor data streams. Different methods from dimension reduction, anomaly detection as well as time series classification are used to automatically detect disturbances combined with a web-based online visualization tool. This enables automated decision-making processes in control centers to mitigate critical system states and to ensure secure system operations (e.g., by activating curate actions). Measurement and simulation-based results are presented to evaluate the proposed synchrophasor application modules for different use cases at the transmission and distribution level.https://www.mdpi.com/2076-3417/10/15/5209disturbance detectiondata compressionpost-mortem analysis |
| spellingShingle | Andre Kummerow Cristian Monsalve Christoph Brosinsky Steffen Nicolai Dirk Westermann A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems Applied Sciences disturbance detection data compression post-mortem analysis |
| title | A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems |
| title_full | A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems |
| title_fullStr | A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems |
| title_full_unstemmed | A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems |
| title_short | A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems |
| title_sort | novel framework for synchrophasor based online recognition and efficient post mortem analysis of disturbances in power systems |
| topic | disturbance detection data compression post-mortem analysis |
| url | https://www.mdpi.com/2076-3417/10/15/5209 |
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