Self-Dispatch of Wind-Storage Integrated System: A Deep Reinforcement Learning Approach

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24227

Title:	Self-Dispatch of Wind-Storage Integrated System: A Deep Reinforcement Learning Approach
Authors:	Wei, X Xiang, Y Li, J Zhang, X
Keywords:	wind farm;energy storage system;electricity market;deep reinforcement learning;distributed prioritized experience replay;maximum entropy
Issue Date:	7-Mar-2022
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Citation:	Wei, X., Xiang, Y., Li, J. and Zhang, X. (2022) 'Self-Dispatch of Wind-Storage Integrated System: A Deep Reinforcement Learning Approach', IEEE Transactions on Sustainable Energy 13 (3), pp. 1861 - 1864. doi: 10.1109/tste.2022.3156426.
URI:	https://bura.brunel.ac.uk/handle/2438/24227 ORCID iDs: Xiangyu Wei https://orcid.org/0000-0003-1436-9303; Yue Xiang https://orcid.org/0000-0001-8456-1195; Xin Zhang https://orcid.org/0000-0002-6063-959X.
DOI:	https://doi.org/10.1109/tste.2022.3156426
ISSN:	1949-3029
Appears in Collections:	Dept of Electronic and Electrical Engineering Research Papers

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