Rapid and Accurate Changepoint Detection of Power System Forced Oscillations
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866917256358789120 |
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| author | Dosiek, Luke Karn, Akaash Liu, Frank |
| author_facet | Dosiek, Luke Karn, Akaash Liu, Frank |
| contents | This paper describes a new approach for using changepoint detection (CPD) to estimate the starting and stopping times of a forced oscillation (FO) in measured power system data. As with a previous application of CPD to this problem, the pruned exact linear time (PELT) algorithm is used. However, instead of allowing PELT to automatically tune its penalty parameter, a method of manually providing it is presented that dramatically reduces computation time without sacrificing accuracy. Additionally, the new algorithm requires fewer input parameters and provides a formal, data-driven approach to setting the minimum FO segment length to consider as troublesome for an electromechanical mode meter. A low-order ARMAX representation of the minniWECC model is used to test the approach, where a 98\% reduction in computation time is enjoyed with high estimation accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_15812 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Rapid and Accurate Changepoint Detection of Power System Forced Oscillations Dosiek, Luke Karn, Akaash Liu, Frank Signal Processing Systems and Control This paper describes a new approach for using changepoint detection (CPD) to estimate the starting and stopping times of a forced oscillation (FO) in measured power system data. As with a previous application of CPD to this problem, the pruned exact linear time (PELT) algorithm is used. However, instead of allowing PELT to automatically tune its penalty parameter, a method of manually providing it is presented that dramatically reduces computation time without sacrificing accuracy. Additionally, the new algorithm requires fewer input parameters and provides a formal, data-driven approach to setting the minimum FO segment length to consider as troublesome for an electromechanical mode meter. A low-order ARMAX representation of the minniWECC model is used to test the approach, where a 98\% reduction in computation time is enjoyed with high estimation accuracy. |
| title | Rapid and Accurate Changepoint Detection of Power System Forced Oscillations |
| topic | Signal Processing Systems and Control |
| url | https://arxiv.org/abs/2511.15812 |