Hybrid Energy Storage Control Based on Prediction and Deep Reinforcement Learning Compensation for Wind Power Smoothing
Author:
Affiliation:
1. School of Electrical and Information Engineering, Hunan University of Technology,Zhuzhou,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10294329/10294332/10294396.pdf?arnumber=10294396
Reference20 articles.
1. Battery ESS Planning for Wind Smoothing via Variable-Interval Reference Modulation and Self-Adaptive SOC Control Strategy
2. Probabilistic Forecasting Based Sizing and Control of Hybrid Energy Storage for Wind Power Smoothing
3. An Extended New Approach for Forecasting Short-Term Wind Power Using Modified Fuzzy Wavelet Neural Network: A Case Study in Wind Power Plant;ghoushchi;Energy,2021
4. Self-Dispatch of Wind-Storage Integrated System: A Deep Reinforcement Learning Approach
5. Continuous control with deep reinforcement learning;lillicrap;Science of Computing,2015
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