A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy
Transient Instability Prediction (TIP) of the synchronous generator offers an opportunity to mitigate out-of-step damages through early tripping or facilitating remedial actions to prevent instability. Analyzing transient stability is inherently complex due to the diverse components and controllers...
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10947679/ |
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| author | Parva Soori Alireza Sobbouhi Mohamma Reza Aghamohammadi Mohamma Sadegh Sepasian |
| author_facet | Parva Soori Alireza Sobbouhi Mohamma Reza Aghamohammadi Mohamma Sadegh Sepasian |
| author_sort | Parva Soori |
| collection | DOAJ |
| description | Transient Instability Prediction (TIP) of the synchronous generator offers an opportunity to mitigate out-of-step damages through early tripping or facilitating remedial actions to prevent instability. Analyzing transient stability is inherently complex due to the diverse components and controllers within the power system, and it must be conducted within a limited timeframe of less than one second. This study introduces an innovative method for predicting the instability of synchronous machines, focusing on the rate of generator energy variations. The energy is calculated using the integral of the electrical power of the generator measured over time. This energy increases during a fault and subsequently decreases in post-fault. The increase in the rate of change of energy in the energy-releasing area indicates that the machine is progressing toward an unstable condition. This novel criterion is implemented locally on each generator within the network, enabling effective prediction of transient instability through the sole measurement of the machine’s electrical power. The proposed approach is online, conceptual, and independent of fault data, network configuration, and system parameters. Furthermore, the reliability level of the proposed method can be determined based on the required accuracy level or prediction speed using a rule-based mechanism. Simulation results across various scenarios in the IEEE 39-bus and Iran power systems demonstrate that the proposed approach effectively predicts the instability condition quickly and precisely. The algorithm is implemented in MATLAB, and Power Factory software is employed as the stability laboratory. |
| format | Article |
| id | doaj-art-6f1d5085c43f4eb3bb620878fffa9fdd |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-6f1d5085c43f4eb3bb620878fffa9fdd2025-08-20T02:20:23ZengIEEEIEEE Access2169-35362025-01-0113705677058010.1109/ACCESS.2025.355721210947679A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator EnergyParva Soori0https://orcid.org/0009-0005-9905-1047Alireza Sobbouhi1https://orcid.org/0000-0001-5037-5968Mohamma Reza Aghamohammadi2https://orcid.org/0000-0002-8556-2218Mohamma Sadegh Sepasian3Electrical Engineering Department, Shahid Beheshti University, Tehran, IranElectrical Engineering Department, Shahid Beheshti University, Tehran, IranElectrical Engineering Department, Shahid Beheshti University, Tehran, IranElectrical Engineering Department, Shahid Beheshti University, Tehran, IranTransient Instability Prediction (TIP) of the synchronous generator offers an opportunity to mitigate out-of-step damages through early tripping or facilitating remedial actions to prevent instability. Analyzing transient stability is inherently complex due to the diverse components and controllers within the power system, and it must be conducted within a limited timeframe of less than one second. This study introduces an innovative method for predicting the instability of synchronous machines, focusing on the rate of generator energy variations. The energy is calculated using the integral of the electrical power of the generator measured over time. This energy increases during a fault and subsequently decreases in post-fault. The increase in the rate of change of energy in the energy-releasing area indicates that the machine is progressing toward an unstable condition. This novel criterion is implemented locally on each generator within the network, enabling effective prediction of transient instability through the sole measurement of the machine’s electrical power. The proposed approach is online, conceptual, and independent of fault data, network configuration, and system parameters. Furthermore, the reliability level of the proposed method can be determined based on the required accuracy level or prediction speed using a rule-based mechanism. Simulation results across various scenarios in the IEEE 39-bus and Iran power systems demonstrate that the proposed approach effectively predicts the instability condition quickly and precisely. The algorithm is implemented in MATLAB, and Power Factory software is employed as the stability laboratory.https://ieeexplore.ieee.org/document/10947679/Differential predictorinstability predictionrate of change of energytransient stability |
| spellingShingle | Parva Soori Alireza Sobbouhi Mohamma Reza Aghamohammadi Mohamma Sadegh Sepasian A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy IEEE Access Differential predictor instability prediction rate of change of energy transient stability |
| title | A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy |
| title_full | A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy |
| title_fullStr | A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy |
| title_full_unstemmed | A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy |
| title_short | A New Approach for Online Transient Instability Assessment and Prediction via Tracing the Variation Trend of Synchronous Generator Energy |
| title_sort | new approach for online transient instability assessment and prediction via tracing the variation trend of synchronous generator energy |
| topic | Differential predictor instability prediction rate of change of energy transient stability |
| url | https://ieeexplore.ieee.org/document/10947679/ |
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