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REST framework: A modelling approach towards cooling energy stress mitigation plans for future cities in warming Global South

Title
REST framework: A modelling approach towards cooling energy stress mitigation plans for future cities in warming Global South
Type
Article in International Scientific Journal
Year
2020
Authors
Bardhan, R
(Author)
Other
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Debnath, R
(Author)
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João Gama
(Author)
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Vijay, U
(Author)
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Journal
Vol. 61
ISSN: 2210-6707
Publisher: Elsevier
Other information
Authenticus ID: P-00S-90M
Abstract (EN): Future cities of the Global South will not only rapidly urbanise but will also get warmer from climate change and urbanisation induced effects. It will trigger a multi-fold increase in cooling demand, especially at a residential level, mitigation to which remains a policy and research gap. This study forwards a novel residential energy stress mitigation framework called REST to estimate warming climate-induced energy stress in residential buildings using a GIS-driven urban heat island and energy modelling approach. REST further estimates rooftop solar potential to enable solar photo-voltaic (PV) based decentralised energy solutions and establish an optimised routine for peer-to-peer energy sharing at a neighbourhood scale. The optimised network is classified through a decision tree algorithm to derive sustainability rules for mitigating energy stress at an urban planning scale. These sustainability rules established distributive energy justice variables in urban planning context. The REST framework is applied as a proof-of-concept on a future smart city of India, named Amaravati. Results show that cooling energy stress can be reduced by 80 % in the study area through sensitive use of planning variables like Floor Space Index (FSI) and built-up density. It has crucial policy implications towards the design and implementation of a national level cooling action plans in the future cities of the Global South to meet the UN-SDG - 7 (clean and affordable energy) and SDG - 11 (sustainable cities and communities) targets.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 18
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