Knowledge Agora



Scientific Article details

Title Low-carbon urban-rural modern energy systems with energy resilience under climate change and extreme events in China-A state-of-the-art review
ID_Doc 27750
Authors Zhou, YK
Title Low-carbon urban-rural modern energy systems with energy resilience under climate change and extreme events in China-A state-of-the-art review
Year 2024
Published
DOI 10.1016/j.enbuild.2024.114661
Abstract Climate-adaptive energy resilience and low-carbon transformation are mainstreams to combat with climate change uncertainty, rural energy poverty, and urban modern energy systems. However, effective strategies have not been provided for energy resilience enhancement considering centralized and decentralized system transition, climate change, extreme weather, natural disasters, equipment failure. In this study, urban and rural energy systems are comprehensively reviewed and compared for low-carbon and sustainability transformation, in terms of energy structures, raw energy sources availability, energy consumption density and carbon emission, accessibility on renewable energy, and etc. Advanced modelling techniques were systematically reviewed for integrated multi-energy systems. Decarbonisation pathways on both urban and rural energy systems were explored. Last but not the least, energy resilience on urban and rural energy systems was studied, including climate change database and modelling techniques, climate change on energy demands and power supply in district energy systems, energy planning strategies for energy resilience enhancement. Research results indicate that, rural areas are abundant in bioenergy (like biogas, biomass, etc), sufficient for renewable system installations, but limited access to modern energy services and energy poverty, while urban cities are characterized with limited spaces for renewable systems, unbalanced cooling/heating loads, and a large amount of waste. Modelling techniques for integrated multi-energy systems mainly include physical models, human knowledge-based machine learning models and data-driven models. The physical models and human knowledge-based machine learning models require specific expertise in physical mechanisms, while the data-driven models are superior in calculation efficiency and user-friendly interface. Energy resilience on urban and rural energy systems is able to ensure a reliable energy supply, and emergency plan to address disruptions from events, like extreme weather and natural disasters. To achieve climate-adaptive energy resilience and low-carbon transformation, main challenges include socio-economic equality access, deployment of charging piles and smart charging development for electric vehicles, battery circular economy in integrated rural-city energy systems, and carbon intensity of battery circular economy. Research results can promote climate-adaptive energy resilience and low-carbon urban modern energy and rural energy poverty systems in China.
Author Keywords Urban-rural modern energy system; Low-carbon transition; Climate change; Energy resilience; Circular economy
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:001311742900001
WoS Category Construction & Building Technology; Energy & Fuels; Engineering, Civil
Research Area Construction & Building Technology; Energy & Fuels; Engineering
PDF
Similar atricles
Scroll