Machine Learning-based Fault Diagnosis for Distribution Networks with Distributed Renewable Energy Resources
Author:
Affiliation:
1. Zhongshan Power Supply Bureau of Guangdong Power Grid Co., Ltd.,Zhongshan,China
2. Power Dispatch and Control Center of Guangdong Power Grid Co., Ltd.,Guangzhou,China
Funder
China Southern Power Grid
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10543251/10544378/10544561.pdf?arnumber=10544561
Reference15 articles.
1. Incipient Fault Detection in Power Distribution System: A Time–Frequency Embedded Deep-Learning-Based Approach
2. Envisioning the Future Renewable and Resilient Energy Grids—A Power Grid Revolution Enabled by Renewables, Energy Storage, and Energy Electronics
3. A Comprehensive Review on Protection Strategies to Mitigate the Impact of Renewable Energy Sources on Interconnected Distribution Networks
4. Probabilistic Physics-Informed Graph Convolutional Network for Active Distribution System Voltage Prediction
5. Protection challenges under bulk penetration of renewable energy resources in power systems: A review
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