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A Power Grid Stability Analysis Method Based on CNN
- 1 School of Electrical Engineering, Northeast Electric Power University
* Author to whom correspondence should be addressed.
Abstract
As power systems' interconnection scale expands, the methods for analyzing power grid stability need further optimization. This paper proposes a power grid stability analysis method based on Convolutional Neural Networks(CNN). We model the power grid stability problem as a binary classification problem. Firstly, we provide a detailed explanation of the power grid characteristic data and conduct data preprocessing. Subsequently, due to the advantages of CNN in processing spatially structured data, we address this problem. Finally, we obtain a new power grid stability analysis model through case-based comparative analysis. The results indicate that the proposed model outperforms traditional analysis methods in terms of classification accuracy, recall rate, and F1-score.
Keywords
Power Grid Stability, Machine Learning, Convolutional Neural Network, Binary Classification
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Cite this article
Pu,X. (2025). A Power Grid Stability Analysis Method Based on CNN. Applied and Computational Engineering,149,20-26.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of CONF-MSS 2025 Symposium: Automation and Smart Technologies in Petroleum Engineering
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