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29 November 2023 Transient stability assessment for power system based on importance evaluation and enhancement of samples
Jiexiang Hu, Qiwei Wang, Shengshuo Chen, Guyu Xu, Yansong Li, Jun Liu, Xinglei Chen
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Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 1293712 (2023) https://doi.org/10.1117/12.3013266
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore
Abstract
Currently, transient stability assessment based on deep learning requires offline generation of a large amount of data to train predictive models. However, when there is insufficient training data, the accuracy of the model's predictions significantly decreases. To address this challenge, this paper proposes a method for selecting and enhancing key samples. Firstly, a quantitative analysis of the correlation between samples and the training of the model and transient stability boundaries is conducted. Based on this analysis, a sample importance index is defined, and key samples are selected based on this index. Then, these key samples are enhanced using Generative Adversarial Networks (GANs) to improve the representation capability of the sample set and help the transient stability model learn classification boundaries that better fit real transient stability boundaries. This method is applied to the New England 10-machine 39-node system and a provincial-level power grid in China. The test results show that with the enhancement of key samples to 10%, the misclassification rate of the predictive model decreased by 86.54%. This approach significantly improves the predictive capability of the model under the condition of limited training samples.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Jiexiang Hu, Qiwei Wang, Shengshuo Chen, Guyu Xu, Yansong Li, Jun Liu, and Xinglei Chen "Transient stability assessment for power system based on importance evaluation and enhancement of samples", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 1293712 (29 November 2023); https://doi.org/10.1117/12.3013266
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KEYWORDS
Statistical modeling
Education and training
Data modeling
Brain-machine interfaces
Machine learning
Sampling rates
Performance modeling
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