Deep generative model for probabilistic wind speed and wind power estimation at a wind farm
Author:
Affiliation:
1. Department of Mechanical Engineering Tokyo Institute of Technology Tokyo Japan
2. College of Atmospheric Science Chengdu University of Information Technology Chengdu China
Funder
National Natural Science Foundation of China
Publisher
Wiley
Subject
General Energy,Safety, Risk, Reliability and Quality
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.1086
Reference66 articles.
1. Assessing the effect of wind power peaking characteristics on the maximum penetration level of wind power
2. A gated recurrent unit neural networks based wind speed error correction model for short-term wind power forecasting
3. Empirical error correction and feature identification for long term wind resource assessment using support vector regression
4. A review on hybrid empirical mode decomposition models for wind speed and wind power prediction;Bokde N;Energies,2019
5. Short-Term Wind Power Generation Forecasting: Direct Versus Indirect Arima-Based Approaches
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