volume 192 pages 114184

A co-simulated material-component-system-district framework for climate-adaption and sustainability transition

Yuekuan Zhou 1, 2, 3, 4
Siqian Zheng 5, 6
Publication typeJournal Article
Publication date2024-03-01
scimago Q1
wos Q1
SJR3.901
CiteScore38.0
Impact factor16.3
ISSN13640321, 18790690
Renewable Energy, Sustainability and the Environment
Abstract
Due to considerable carbon emissions in building sectors, sustainability transformation is essential for power supply reliability, stability, grid-friendly interaction, and integration with e-transportation. However, building sustainability transformation requires inter-disciplinary and trans-disciplinary platforms for ‘material-component-building-district’ co-simulations and innovations. In this study, a generic methodology is proposed to comprehensively interconnect nano-scale material and energy systems in thermal transport and thermodynamics, guiding the design and operation for lifecycle sustainability, together with carbon intensity quantification and decarbonisation potential. Afterwards, a cross-scale energy simulation platform is formulated, involving nanoporous materials, innovative components, building integrations, and district energy analytics. The formulated platform can enable synthetical and comprehensive analysis on thermodynamic performances, energy performances, energy conversion and management, throughout integrated cross-disciplinary approaches by overcoming performance overestimation or underestimation of traditional single-stage approaches. The application of the platform quantifies the decreasing magnitude of energy consumption for PCM microcapsule wall, self-cleaning façade coating, clear thermal resistant cleaning glass coating, evaporative cooling & solar PV roof, volatile organic compound (VOC) absorption for indoor air quality (IAQ) control, building integrated photovoltaics (BIPVs), solar thermal collectors and 10-kW wind turbine. Afterwards, dynamic interaction between real buildings and digital twin models was realized for fast computation and prediction, labour cost and initial investment cost saving, long-term performance analysis. Both historical database and digital twin-generated database can promote the development of machine learning (ML) models, through data preparation, hyperparameter optimization, model training, testing, and validation. The proposed approach and formulated platform can enable synthetical and comprehensive analysis on building sustainability, throughout integrated cross-disciplinary approaches for 2060 carbon neutrality in China.
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GOST |
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GOST Copy
Zhou Y. et al. A co-simulated material-component-system-district framework for climate-adaption and sustainability transition // Renewable and Sustainable Energy Reviews. 2024. Vol. 192. p. 114184.
GOST all authors (up to 50) Copy
Zhou Y., Zheng S. A co-simulated material-component-system-district framework for climate-adaption and sustainability transition // Renewable and Sustainable Energy Reviews. 2024. Vol. 192. p. 114184.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1016/j.rser.2023.114184
UR - https://linkinghub.elsevier.com/retrieve/pii/S1364032123010420
TI - A co-simulated material-component-system-district framework for climate-adaption and sustainability transition
T2 - Renewable and Sustainable Energy Reviews
AU - Zhou, Yuekuan
AU - Zheng, Siqian
PY - 2024
DA - 2024/03/01
PB - Elsevier
SP - 114184
VL - 192
SN - 1364-0321
SN - 1879-0690
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Zhou,
author = {Yuekuan Zhou and Siqian Zheng},
title = {A co-simulated material-component-system-district framework for climate-adaption and sustainability transition},
journal = {Renewable and Sustainable Energy Reviews},
year = {2024},
volume = {192},
publisher = {Elsevier},
month = {mar},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1364032123010420},
pages = {114184},
doi = {10.1016/j.rser.2023.114184}
}