Wide Area Based Online Transient Stability Prediction Using Regression Model
It is essential to assess the transient stability status of any power system quickly and effectively after a significant disturbance in order to plan and implement the required corrective control procedures. PMUs enable for synchronised measurements of essential system variables from physically scat...
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Published in | 2022 IEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE) Vol. 7; pp. 433 - 437 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.12.2022
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Subjects | |
Online Access | Get full text |
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Summary: | It is essential to assess the transient stability status of any power system quickly and effectively after a significant disturbance in order to plan and implement the required corrective control procedures. PMUs enable for synchronised measurements of essential system variables from physically scattered locations in wide-area monitoring systems, which could be utilised for measurement-centered transient stability analysis. A post-fault online transient stability assessment (TSA) approach using wide area synchrophasor data is presented in this paper. Using during fault wide-area bus voltage measurements, regression model predicts the system's transient stability state in the form of normalized transient stability margin (TSM). Important features of the proposed work are PMU placement and prediction of transient stability status immediately after fault clearance using only during fault measurements. The predicted normalized transient stability margin not only classifies the contingency but also gives the quantitative analysis of stability status. The proposed TSA approach has been evaluated using New England (NE) 39 bus test system. |
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DOI: | 10.1109/ICRAIE56454.2022.10054249 |