Probabilistic Power Flow of Distribution System Based on a Graph-Aware Deep Learning Network
Author:
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9621343/9621368/09621647.pdf?arnumber=9621647
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Congestion forecast framework based on probabilistic power flow and machine learning for smart distribution grids;International Journal of Electrical Power & Energy Systems;2024-02
2. A Novel Sequence to Sequence Data Modelling Based CNN-LSTM Algorithm for Three Years Ahead Monthly Peak Load Forecasting;IEEE Transactions on Power Systems;2024-01
3. A Robust Data-Driven Process Modeling Applied to Time-Series Stochastic Power Flow;IEEE Transactions on Power Systems;2024-01
4. Graph Attention Enabled Convolutional Network for Distribution System Probabilistic Power Flow;IEEE Transactions on Industry Applications;2022-11
5. Fast DC Optimal Power Flow Based on Deep Convolutional Neural Network;2022 IEEE 5th International Electrical and Energy Conference (CIEEC);2022-05-27
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