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Transient voltage stability assessment based on transfer learning for small samples
  • +3
  • Jiayi Zhang,
  • Hui Ren,
  • Xi Wang,
  • zheng zhibin,
  • Jinling Lu,
  • Fei Wang
Jiayi Zhang
North China Electric Power University - Baoding Campus
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Hui Ren
North China Electric Power University - Baoding Campus

Corresponding Author:[email protected]

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Xi Wang
North China Electric Power University - Baoding Campus
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zheng zhibin
State Grid Shandong Electric Power Company
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Jinling Lu
North China Electric Power University - Baoding Campus
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Fei Wang
North China Electric Power University
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Large penetration of renewable energy sources into the power grid has increased the complexity of power system operation and greatly reduced the ability of the system to withstand large disturbances. The frequent occurrence of voltage instability problems in the power grid has brought new challenges to the assessment of transient stability analysis of the power system. To achieve fast and accurate assessment of transient voltages, a transfer learning-based transient voltage stability assessment with small samples is proposed, introducing a domain transfer learning approach, embedding a cooperative attention mechanism in the residual network during the feature extraction stage to capture long-range correlations between features, and using adversarial approaches to reduce the differences between samples from different data sets, using the source domain to guide the target domain for network training to improve model's evaluation capability when the number of samples is insufficient, enhance the generalisation performance of the network, and effectively improve the performance of real-time power system transient voltage stability evaluation in the absence of sufficient historical data. Testing on an improved New England 39-node system validates the superiority of this method in transient voltage stability assessment and provides a new approach to practical field transient voltage stability assessment.
09 Mar 2023Submitted to IET Generation, Transmission & Distribution
10 Mar 2023Assigned to Editor
10 Mar 2023Submission Checks Completed
14 Mar 2023Reviewer(s) Assigned
08 Apr 2023Review(s) Completed, Editorial Evaluation Pending
08 Apr 2023Editorial Decision: Revise Major