Wind Power Probability Density Prediction Based on Quantile Regression Model of Dilated Causal Convolutional Neural Network-Reference-Cited by-同舟云学术

Wind Power Probability Density Prediction Based on Quantile Regression Model of Dilated Causal Convolutional Neural Network

Author:

Yang Yunhao¹,Zhang Heng²,Peng Shurong³,Su Sheng³,Li Bin³

Affiliation:

1. College of Computer Science and Technology, Zhejiang University,Hangzhou,China,310058

2. State Grid Jining Electric Power Corporation,Jining,China,272100

3. School of Electrical & Information Engineering, Changsha University of Science & Technology,Changsha,China,410114

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

Reference19 articles.

2. Interval prediction for wind power based on conditional copula function;lan;Proceedings of the CSEE,0

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5. High-Precision Wind Power Output Data Recovery Based on MA-Bi-LSTM;2024 IEEE 2nd International Conference on Power Science and Technology (ICPST);2024-05-09