Novel data-driven energy management of a hybrid photovoltaic-reverse osmosis desalination system using deep reinforcement learning
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DOI: 10.1016/j.apenergy.2022.119184
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Cited by:
- Jiankai Gao & Yang Li & Bin Wang & Haibo Wu, 2023. "Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm," Energies, MDPI, vol. 16(7), pages 1-21, April.
- Elsir, Mohamed & Al-Sumaiti, Ameena Saad & El Moursi, Mohamed Shawky & Al-Awami, Ali Taleb, 2023. "Coordinating the day-ahead operation scheduling for demand response and water desalination plants in smart grid," Applied Energy, Elsevier, vol. 335(C).
- Xu, Jiacheng & Liang, Yingzong & Luo, Xianglong & Chen, Jianyong & Yang, Zhi & Chen, Ying, 2023. "Towards cost-effective osmotic power harnessing: Mass exchanger network synthesis for multi-stream pressure-retarded osmosis systems," Applied Energy, Elsevier, vol. 330(PA).
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Keywords
Energy management; Deep reinforcement learning; Actor-critic methods; Partially observable Markov decision process; Reverse osmosis; Pressure retarded osmosis;All these keywords.
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