- Tytuł:
- Identification method for power quality disturbances in distribution network based on transfer learning
- Autorzy:
-
Heping, Peng
Wenxiong, Mo
Yong, Wang
Le, Luan
Zhong, Xu - Powiązania:
- https://bibliotekanauki.pl/articles/2135730.pdf
- Data publikacji:
- 2022
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
disturbance identification
distribution network
multiple transfer learning
power quality - Opis:
- For a higher classification accuracy of disturbance signals of power quality, a disturbance classification method for power quality based on gram angle field and multiple transfer learning is proposed in this paper. Firstly, the one-dimensional disturbance signal of power quality is transformed into a Gramian angular field (GAF) coded image by using the gram angle field, and then three ResNet networks are constructed. The disturbance signals with representative signal-to-noise ratios of 0 dB, 20 dB and 40 dB are selected as the input of the sub-model to train the three sub-models, respectively. During this period, the training weights of the sub-models are transferred in turn by using the method of multiple transfer learning. The pre-training weight of the latter model is inherited from the training weight of the previous model, and the weight processing methods of partial freezing and partial fine-tuning are adopted to ensure the optimal training effect of the model. Finally, the features of the three sub-models are fused to train the classifier with a full connection layer, and a disturbance classification model for power quality is obtained. The simulation results show that the method has higher classification accuracy and better anti-noise performance, and the proposed model has good robustness and generalization.
- Źródło:
-
Archives of Electrical Engineering; 2022, 71, 3; 731--754
1427-4221
2300-2506 - Pojawia się w:
- Archives of Electrical Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł