Improving Energy Management through Demand Response Programs for Low-Rise University Buildings
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- Qu, Zhijian & Xu, Juan & Wang, Zixiao & Chi, Rui & Liu, Hanxin, 2021. "Prediction of electricity generation from a combined cycle power plant based on a stacking ensemble and its hyperparameter optimization with a grid-search method," Energy, Elsevier, vol. 227(C).
- Zhao, Bochao & Ye, Minxiang & Stankovic, Lina & Stankovic, Vladimir, 2020. "Non-intrusive load disaggregation solutions for very low-rate smart meter data," Applied Energy, Elsevier, vol. 268(C).
- Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
- Shi, Xin & Ming, Hao & Shakkottai, Srinivas & Xie, Le & Yao, Jianguo, 2019. "Nonintrusive load monitoring in residential households with low-resolution data," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
- Fathi, Soheil & Srinivasan, Ravi & Fenner, Andriel & Fathi, Sahand, 2020. "Machine learning applications in urban building energy performance forecasting: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
- Mohammad Shakeri & Jagadeesh Pasupuleti & Nowshad Amin & Md. Rokonuzzaman & Foo Wah Low & Chong Tak Yaw & Nilofar Asim & Nurul Asma Samsudin & Sieh Kiong Tiong & Chong Kok Hen & Chin Wei Lai, 2020. "An Overview of the Building Energy Management System Considering the Demand Response Programs, Smart Strategies and Smart Grid," Energies, MDPI, vol. 13(13), pages 1-15, June.
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- Bustos, Roberto & Marín, Luis G. & Navas-Fonseca, Alex & Reyes-Chamorro, Lorenzo & Sáez, Doris, 2023. "Hierarchical energy management system for multi-microgrid coordination with demand-side management," Applied Energy, Elsevier, vol. 342(C).
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