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Scalable coordinated management of peer-to-peer energy trading: A multi-cluster deep reinforcement learning approach

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Cited by:

  1. Zhou, Quan & Li, Yanfei & Zhao, Dezong & Li, Ji & Williams, Huw & Xu, Hongming & Yan, Fuwu, 2022. "Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression," Applied Energy, Elsevier, vol. 305(C).
  2. Spyros Giannelos & Stefan Borozan & Marko Aunedi & Xi Zhang & Hossein Ameli & Danny Pudjianto & Ioannis Konstantelos & Goran Strbac, 2023. "Modelling Smart Grid Technologies in Optimisation Problems for Electricity Grids," Energies, MDPI, vol. 16(13), pages 1-15, June.
  3. Spiliopoulos, Nikolas & Sarantakos, Ilias & Nikkhah, Saman & Gkizas, George & Giaouris, Damian & Taylor, Phil & Rajarathnam, Uma & Wade, Neal, 2022. "Peer-to-peer energy trading for improving economic and resilient operation of microgrids," Renewable Energy, Elsevier, vol. 199(C), pages 517-535.
  4. Pinto, Giuseppe & Kathirgamanathan, Anjukan & Mangina, Eleni & Finn, Donal P. & Capozzoli, Alfonso, 2022. "Enhancing energy management in grid-interactive buildings: A comparison among cooperative and coordinated architectures," Applied Energy, Elsevier, vol. 310(C).
  5. Qiu, Dawei & Wang, Yi & Hua, Weiqi & Strbac, Goran, 2023. "Reinforcement learning for electric vehicle applications in power systems:A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
  6. Wang, Yi & Qiu, Dawei & Strbac, Goran, 2022. "Multi-agent deep reinforcement learning for resilience-driven routing and scheduling of mobile energy storage systems," Applied Energy, Elsevier, vol. 310(C).
  7. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
  8. Samende, Cephas & Cao, Jun & Fan, Zhong, 2022. "Multi-agent deep deterministic policy gradient algorithm for peer-to-peer energy trading considering distribution network constraints," Applied Energy, Elsevier, vol. 317(C).
  9. Demir, Sumeyra & Stappers, Bart & Kok, Koen & Paterakis, Nikolaos G., 2022. "Statistical arbitrage trading on the intraday market using the asynchronous advantage actor–critic method," Applied Energy, Elsevier, vol. 314(C).
  10. Zeng, Lanting & Qiu, Dawei & Sun, Mingyang, 2022. "Resilience enhancement of multi-agent reinforcement learning-based demand response against adversarial attacks," Applied Energy, Elsevier, vol. 324(C).
  11. Qiu, Dawei & Dong, Zihang & Zhang, Xi & Wang, Yi & Strbac, Goran, 2022. "Safe reinforcement learning for real-time automatic control in a smart energy-hub," Applied Energy, Elsevier, vol. 309(C).
  12. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan & Cui, Chuanshi, 2024. "Peer-to-peer energy sharing model considering multi-objective optimal allocation of shared energy storage in a multi-microgrid system," Energy, Elsevier, vol. 288(C).
  13. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
  14. Qiu, Dawei & Wang, Yi & Wang, Junkai & Jiang, Chuanwen & Strbac, Goran, 2023. "Personalized retail pricing design for smart metering consumers in electricity market," Applied Energy, Elsevier, vol. 348(C).
  15. Pinthurat, Watcharakorn & Surinkaew, Tossaporn & Hredzak, Branislav, 2024. "An overview of reinforcement learning-based approaches for smart home energy management systems with energy storages," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
  16. Zhou, Xinlei & Du, Han & Xue, Shan & Ma, Zhenjun, 2024. "Recent advances in data mining and machine learning for enhanced building energy management," Energy, Elsevier, vol. 307(C).
  17. Michalakopoulos, Vasilis & Sarmas, Elissaios & Papias, Ioannis & Skaloumpakas, Panagiotis & Marinakis, Vangelis & Doukas, Haris, 2024. "A machine learning-based framework for clustering residential electricity load profiles to enhance demand response programs," Applied Energy, Elsevier, vol. 361(C).
  18. Shama Naz Islam, 2024. "A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies," Energies, MDPI, vol. 17(7), pages 1-18, April.
  19. Shang, Yitong & Yu, Hang & Niu, Songyan & Shao, Ziyun & Jian, Linni, 2021. "Cyber-physical co-modeling and optimal energy dispatching within internet of smart charging points for vehicle-to-grid operation," Applied Energy, Elsevier, vol. 303(C).
  20. Omar Al-Ani & Sanjoy Das, 2022. "Reinforcement Learning: Theory and Applications in HEMS," Energies, MDPI, vol. 15(17), pages 1-37, September.
  21. Zhou, Yanting & Ma, Zhongjing & Shi, Xingyu & Zou, Suli, 2024. "Multi-agent optimal scheduling for integrated energy system considering the global carbon emission constraint," Energy, Elsevier, vol. 288(C).
  22. Homod, Raad Z. & Togun, Hussein & Kadhim Hussein, Ahmed & Noraldeen Al-Mousawi, Fadhel & Yaseen, Zaher Mundher & Al-Kouz, Wael & Abd, Haider J. & Alawi, Omer A. & Goodarzi, Marjan & Hussein, Omar A., 2022. "Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings," Applied Energy, Elsevier, vol. 313(C).
  23. Liu, Jia & Yang, Hongxing & Zhou, Yuekuan, 2021. "Peer-to-peer trading optimizations on net-zero energy communities with energy storage of hydrogen and battery vehicles," Applied Energy, Elsevier, vol. 302(C).
  24. Qiu, Dawei & Xue, Juxing & Zhang, Tingqi & Wang, Jianhong & Sun, Mingyang, 2023. "Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading," Applied Energy, Elsevier, vol. 333(C).
  25. Liangyi Pu & Song Wang & Xiaodong Huang & Xing Liu & Yawei Shi & Huiwei Wang, 2022. "Peer-to-Peer Trading for Energy-Saving Based on Reinforcement Learning," Energies, MDPI, vol. 15(24), pages 1-16, December.
  26. Qiu, Dawei & Wang, Yi & Sun, Mingyang & Strbac, Goran, 2022. "Multi-service provision for electric vehicles in power-transportation networks towards a low-carbon transition: A hierarchical and hybrid multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 313(C).
  27. Javier Parra-Domínguez & Esteban Sánchez & Ángel Ordóñez, 2023. "The Prosumer: A Systematic Review of the New Paradigm in Energy and Sustainable Development," Sustainability, MDPI, vol. 15(13), pages 1-44, July.
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