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| 中国省级相对能源贫困测度与分级预警研究 |
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周德群1,2,赵斯琪1,2,周婧颖3,刘欣颖3,丁浩1,2
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(1.南京航空航天大学 经济与管理学院,江苏 南京 210016;2.南京航空航天大学 能源软科学中心,江苏 南京 210016;3.南京航空航天大学 数学学院,江苏 南京 210016)
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| 摘要: |
| 相对贫困已经成为中国贫困的主要表现形式。在能源领域,中国已消除初级阶段的绝对能源贫困,但用能水平低、用能结构差、用能能力弱等现象所反映的相对能源贫困问题仍广泛存在。基于能源贫困定义和相关理论分析,从可获得性、可负担性、可靠性和可持续性4个维度构建相对能源贫困指数,对2010—2021年中国各省份相对能源贫困水平进行测度；并利用k-means算法对各省份相对能源贫困水平进行聚类,根据数据特征提出了分区域、分等级的相对能源贫困预警标准。结果显示,在时间演化方面,2010—2021年间全国平均相对能源贫困指数呈下降趋势；在空间分布方面,相对能源贫困水平呈现“西高东低,北高南低”的特征,吉林、黑龙江、贵州、西藏、甘肃、青海和宁夏7个省份为能源贫困红色预警区域。据此,提出政策建议:(1)构建相对能源贫困治理过渡保障机制；(2)建立相对能源贫困区域一体化削减体系；(3)完善相对能源贫困动态分区分级阶段性预警标准。 |
| 关键词: 相对能源贫困 多维指数 统计测度 分级预警 |
| DOI：10.13216/j.cnki.upcjess.2023.05.0004 |
| 分类号:F426.2 |
| 基金项目:国家社会科学基金重大项目(22ZDA113) |
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| China 's Provincial Relative Energy Poverty Measurement and Grading Early Warning |
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ZHOU Dequn1,2, ZHAO Siqi1,2, ZHOU Jingying3, LIU Xinying3, DING Hao1,2
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(1.College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106,Jiangsu,China;2.Research Center for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, Nanjing 211106,Jiangsu,China;3.School of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106,Jiangsu,China)
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| Abstract: |
| Relative poverty has become the main form of poverty in China. In the field of energy, China has eliminated the absolute energy poverty in the primary stage. But the relative energy poverty reflected by the low level of energy use, poor energy structure and weak energy use capacity still widely exists. Based on the definition of energy poverty and relevant theoretical analysis, this study constructed a relative energy poverty index from the four dimensions of availability, affordability, reliability and sustainability. It was used to measure the relative energy poverty level of China 's provinces from 2010 to 2021. Further, the k-means algorithm was used to cluster the relative energy poverty level of each province. We also proposed a regional and hierarchical relative energy poverty early warning standard based on the data characteristics. The results show that in terms of time evolution, the national average relative energy poverty index shows a downward trend from 2010 to 2021. In terms of spatial distribution, the relative energy poverty level shows regional characteristics of "high in the west and low in the east, high in the north and low in the south". Jilin, Heilongjiang, Guizhou, Tibet, Gansu, Qinghai and Ningxia are red warning areas of relative energy poverty. Based on this, we proposed three policy implications. Firstly, it is necessary to build a transitional guarantee mechanism for relative energy poverty governance in China. Secondly, the governments can establish a regional integrated reduction system for relative energy poverty. Thirdly, it is important to improve the dynamic zoning and staged early warning standards for relative energy poverty. |
| Key words: relative energy poverty multidimensional index statistical measurement graded early warning 英文编校:马志强 |
