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Energy assessment in rural regions of China with various scenarios: Historical–to–futuristic.

Authors :
Yang, Chengying
Li, Mingming
Zhou, Dianyi
Source :
Energy. Sep2024, Vol. 302, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Approximately 172 million rural households in China in 2022, will still rely on traditional biofuels instead of electricity. This study explores the feasibility of achieving rural electrification in China utilization various Energy origins and assesses its potential impact on climate change mitigation. To do so, we employ the Regional Energy Model (REM) to formulate hypotheses for rural power distribution. Covering the era from 2020 until 2050. We evaluate consequences in terms of greenhouse gas discharges, principal energy consumption, associated expenses by comparing these possibilities with a Business- as -Usual (BU) scenario. Our findings reveal that diesel-based arrangements tend to produce 'the maximum Carbon Dioxide (CO2) emissions, trailed by network-based solutions. Electrification focused on renewable energy-driven applications has the potential to reduce total CO2 emissions by up to 97 % and primary energy consumption by 43 % in 2050 compared to the BU scenario. We also find that electrification through decentralized diesel systems tends to be the priciest choice. Rural electrification utilizing renewable energy emerges as a cost-effective choice when the majority of end-use applications rely on renewable energy sources. However, it becomes less economical than network expansions when electric end-user appliances are predominant. In summary, this study investigates the viability of renewable energy for rural power distribution and its role in climate change abatement in rural China, offering policy suggestions. • Analyzes six energy-based scenarios for China's rural electrification until 2050. • Evaluates GHG emissions, energy use, and costs impacts with regional energy model. • Provides policy insights and uncertainties for China's sustainability goals. • An oil price and distance-based analysis also is done with extra 6 scenarios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
302
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
177859274
Full Text :
https://doi.org/10.1016/j.energy.2024.131894