Data-driven control of wind turbine under online power strategy via deep learning and reinforcement learning-Reference-Cited by-同舟云学术

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Data-driven control of wind turbine under online power strategy via deep learning and reinforcement learning

Published:2024-11 Issue: Volume:234 Page:121265
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Li Tenghui^ORCID,Yang Jin^ORCID,Ioannou Anastasia

Publisher

Elsevier BV

Reference53 articles.

1. Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control;Chen;Renew. Energy,2019

2. Implementation and evaluation of control strategies based on an open controller for a 10 MW floating wind turbine;Hu;Renew. Energy,2021

3. Active power dispatch optimization for offshore wind farms considering fatigue distribution;Liao;Renew. Energy,2020

4. Study on aerodynamic performance and wake characteristics of a floating offshore wind turbine under pitch motion;Fu;Renew. Energy,2023

5. A novel MPPT PI discrete reverse-acting controller for a wind energy conversion system;González-Hernández;Renew. Energy,2021

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. Research on data augmentation and synthetic sample quantity uncertainty in few-shot wind power prediction based on the adaptive CRITIC-HLICRVFL method;Renewable Energy;2025-10

2. Economic and stable scheduling strategy for electricity-thermal-hydrogen-gas integrated energy systems based on online MPC under dynamic supply-demand interaction;Renewable Energy;2025-08

3. Model predictive control of wind turbine based on deep-dive holistic observer of tower top IMU;Applied Energy;2025-08

4. Tracking Control of CSTRs Based on Improved OU Noise and the TD3 Algorithm;IEEE Access;2025

5. A Review of the Reinforcement Learning for Wind Farm Operation and Control;2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2);2024-11-29

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