Research on Different Energy Transition Pathway Analysis and Low-Carbon Electricity Development: A Case Study of an Energy System in Inner Mongolia

被引:0
作者
Li, Boyi [1 ]
Cong, Richao [2 ]
Matsumoto, Toru [3 ]
Li, Yajuan [3 ]
机构
[1] Univ Kitakyushu, Grad Sch Environm Engn, Fukuoka 8080135, Japan
[2] Shizuoka Univ Art & Culture, Grad Sch Cultural Policy & Management, Shizuoka 4308533, Japan
[3] Univ Kitakyushu, Inst Environm Sci & Technol, Fukuoka 8080135, Japan
关键词
energy transition; carbon reduction; low-carbon electricity; scenarios analysis; CHINA; STORAGE; EFFICIENCY;
D O I
10.3390/en18123129
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
To achieve carbon neutrality targets in the power sector, regions with rich coal and renewable energy resources are facing unprecedented pressure. This paper explores the decarbonization pathway in the power sector in Inner Mongolia, China, under different energy transition scenarios based on the Long-Range Energy Alternatives Planning System (LEAP) model. This includes renewable energy expansion, carbon capture and storage (CCS) applications, demand response, and economic regulation scenarios. Subsequently, a combination of the Logarithmic Mean Divisia Index (LMDI) and Slack-Based Measure Data Envelopment Analysis (SBM-DEA) model was developed to investigate the influencing factors and power generation efficiency in low-carbon electricity. The results revealed that this region emphasizes first developing renewable energy and improving the carbon and green electricity market and then accelerating CCS technology. Its carbon emissions are among the lowest, at about 77.29 million tons, but the cost could reach CNY 229.8 billion in 2060. We also found that the influencing factors of carbon productivity, low-carbon electricity structures, and carbon emissions significantly affected low-carbon electricity generation; their cumulative contribution rate is 367-588%, 155-399%, and -189--737%, respectively. Regarding low-carbon electricity efficiency, the demand response scenario is the lowest at about 0.71; other scenarios show similar efficiency values. This value could be improved by optimizing the energy consumption structure and the installed capacity configuration.
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页数:25
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