Training of an ANN Feed-Forward Regression Model to Predict Wind Farm Power Production for the Purpose of Active Wake Control
Author:
Affiliation:
1. Institute for Power Systems Technology and Power Mechatronics Ruhr University Bochum,Bochum,Germany,44801
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9842860/9842863/09842992.pdf?arnumber=9842992
Reference19 articles.
1. Wind power plant prediction by using neural networks
2. Estimating the wake losses in large wind farms: A machine learning approach
3. Cooperative Wind Farm Control With Deep Reinforcement Learning and Knowledge-Assisted Learning
4. Distributed Operation of Wind Farm for Maximizing Output Power: A Multi-Agent Deep Reinforcement Learning Approach
5. Comparative performance of AI methods for wind power forecast in Portugal
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1. An Artificial Neural Network-Based Approach to Improve Non-Destructive Asphalt Pavement Density Measurement with an Electrical Density Gauge;Metrology;2024-06-12
2. Implementation of an Advanced Operation Control for AI-based Wind Farm Power Maximization Using Wake Redirection and Artificial Neural Networks;IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society;2022-10-17
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