Decision tree-based optimization for flexibility management for sustainable energy microgrids
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DOI: 10.1016/j.apenergy.2021.116772
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- Holjevac, Ninoslav & Capuder, Tomislav & Zhang, Ning & Kuzle, Igor & Kang, Chongqing, 2017. "Corrective receding horizon scheduling of flexible distributed multi-energy microgrids," Applied Energy, Elsevier, vol. 207(C), pages 176-194.
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Cited by:
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- Huang, Guizao & Wu, Guangning & Yang, Zefeng & Chen, Xing & Wei, Wenfu, 2023. "Development of surrogate models for evaluating energy transfer quality of high-speed railway pantograph-catenary system using physics-based model and machine learning," Applied Energy, Elsevier, vol. 333(C).
- João Faria & Carlos Marques & José Pombo & Sílvio Mariano & Maria do Rosário Calado, 2023. "Optimal Sizing of Renewable Energy Communities: A Multiple Swarms Multi-Objective Particle Swarm Optimization Approach," Energies, MDPI, vol. 16(21), pages 1-33, October.
- Sun, Chu & Ali, Syed Qaseem & Joos, Geza & Paquin, Jean-Nicolas & Montenegro, Juan Felipe Patarroyo, 2023. "Design and CHIL testing of microgrid controller with general rule-based dispatch," Applied Energy, Elsevier, vol. 345(C).
- Romain Mannini & Julien Eynard & Stéphane Grieu, 2022. "A Survey of Recent Advances in the Smart Management of Microgrids and Networked Microgrids," Energies, MDPI, vol. 15(19), pages 1-37, September.
- Mehmet Efe Biresselioglu & Muhittin Hakan Demir, 2022. "Constructing a Decision Tree for Energy Policy Domain Based on Real-Life Data," Energies, MDPI, vol. 15(7), pages 1-15, March.
- Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
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Keywords
Decision tree; Economic dispatch; Flexibility; Machine learning; Microgrid; Microgrid controller;All these keywords.
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