Cloud and machine learning experiments applied to the energy management in a microgrid cluster
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DOI: 10.1016/j.apenergy.2021.117770
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References listed on IDEAS
- Ziba Rostami & Sajad Najafi Ravadanegh & Navid Taghizadegan Kalantari & Josep M. Guerrero & Juan C. Vasquez, 2020. "Dynamic Modeling of Multiple Microgrid Clusters Using Regional Demand Response Programs," Energies, MDPI, vol. 13(16), pages 1-19, August.
- Sang-Ji Lee & Jin-Young Choi & Hyung-Joo Lee & Dong-Jun Won, 2017. "Distributed Coordination Control Strategy for a Multi-Microgrid Based on a Consensus Algorithm," Energies, MDPI, vol. 10(7), pages 1-16, July.
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Cited by:
- Ronaldo Silveira Junior, Jose & Conrado, Bruna R.P. & Matheus dos Santos Alonso, Augusto & Iglesias Brandao, Danilo, 2023. "Interoperability of single-controllable clusters: Aggregate response of low-voltage microgrids," Applied Energy, Elsevier, vol. 340(C).
- Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
- Hugo Gaspar Hernandez-Palma & Jonny Rafael Plaza Alvarado & Jesús Enrique GarcÃa Guiliany & Guilherme Luiz Dotto & Claudete Gindri Ramos, 2024. "Implications of Machine Learning in the Generation of Renewable Energies in Latin America from a Globalized Vision: A Systematic Review," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 1-10, March.
- Sana Qaiyum & Martin Margala & Pravin R. Kshirsagar & Prasun Chakrabarti & Kashif Irshad, 2023. "Energy Performance Analysis of Photovoltaic Integrated with Microgrid Data Analysis Using Deep Learning Feature Selection and Classification Techniques," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
- Arafat, M.Y. & Hossain, M.J. & Alam, Md Morshed, 2024. "Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
- Qiang Wang & Dong Yu & Jinyu Zhou & Chaowu Jin, 2023. "Data Storage Optimization Model Based on Improved Simulated Annealing Algorithm," Sustainability, MDPI, vol. 15(9), pages 1-18, April.
- Tostado-Véliz, Marcos & Hasanien, Hany M. & Jordehi, Ahmad Rezaee & Turky, Rania A. & Jurado, Francisco, 2023. "Risk-averse optimal participation of a DR-intensive microgrid in competitive clusters considering response fatigue," Applied Energy, Elsevier, vol. 339(C).
- Rosero, D.G. & Sanabria, E. & Díaz, N.L. & Trujillo, C.L. & Luna, A. & Andrade, F., 2023. "Full-deployed energy management system tested in a microgrid cluster," Applied Energy, Elsevier, vol. 334(C).
- Erdal Irmak & Ersan Kabalci & Yasin Kabalci, 2023. "Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity," Energies, MDPI, vol. 16(12), pages 1-58, June.
- Muqing Wu & Qingsu He & Yuping Liu & Ziqiang Zhang & Zhongwen Shi & Yifan He, 2022. "Machine Learning Techniques for Decarbonizing and Managing Renewable Energy Grids," Sustainability, MDPI, vol. 14(21), pages 1-13, October.
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Keywords
Cloud computing; Machine learning; Energy management system; Prosumer; Microgrid clustering; Renewable energy;All these keywords.
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