A Residential House Comparative Case Study Using Market Available Smart Plugs and EnAPlugs with Shared Knowledge
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- Liu, Guodong & Jiang, Tao & Ollis, Thomas B. & Zhang, Xiaohu & Tomsovic, Kevin, 2019. "Distributed energy management for community microgrids considering network operational constraints and building thermal dynamics," Applied Energy, Elsevier, vol. 239(C), pages 83-95.
- Almada, J.B. & Leão, R.P.S. & Sampaio, R.F. & Barroso, G.C., 2016. "A centralized and heuristic approach for energy management of an AC microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1396-1404.
- Wang, Zeyu & Srinivasan, Ravi S., 2017. "A review of artificial intelligence based building energy use prediction: Contrasting the capabilities of single and ensemble prediction models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 796-808.
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Keywords
distributed optimization; energy management system; shared knowledge; smart plugs;All these keywords.
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