The City as a Power Hub for Boosting Renewable Energy Communities: A Case Study in Naples
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- Aruta, Giuseppe & Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria, 2023. "Sustainability and energy communities: Assessing the potential of building energy retrofit and renewables to lead the local energy transition," Energy, Elsevier, vol. 282(C).
- Perwez, Usama & Yamaguchi, Yohei & Ma, Tao & Dai, Yanjun & Shimoda, Yoshiyuki, 2022. "Multi-scale GIS-synthetic hybrid approach for the development of commercial building stock energy model," Applied Energy, Elsevier, vol. 323(C).
- Wang, Meng & Yu, Hang & Liu, Yupeng & Lin, Jianyi & Zhong, Xianzhun & Tang, Yin & Guo, Haijin & Jing, Rui, 2024. "Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling," Applied Energy, Elsevier, vol. 366(C).
- Ali, Usman & Shamsi, Mohammad Haris & Bohacek, Mark & Purcell, Karl & Hoare, Cathal & Mangina, Eleni & O’Donnell, James, 2020. "A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making," Applied Energy, Elsevier, vol. 279(C).
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Keywords
urban energy districts; energy performance; urban planning; sustainable urban growth; buildings optimization; decarbonization;All these keywords.
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