长江流域资源与环境 >> 2014, Vol. 23 >> Issue (04): 482-.doi: 10.11870/cjlyzyyhj201404006

• 自然资源 • 上一篇    下一篇

基于信息熵的省域内能源消费总量分配研究

刘红琴, 丁哲, 王泳璇, 段海燕, 王宪恩   

  1. (1.吉林大学地下水资源与环境教育部重点实验室,吉林 长春 130012;2.昆明理工大学管理与经济学院,云南 昆明 650093)
  • 出版日期:2014-04-20

STUDY ON ENERGY CONSUMPTION ALLOCATION WITHIN ONE PROVINCE BASED ON INFORMATION ENTROPY

LIU Hongqin1,2, DING Zhe1,WANG Yongxuan1, DUAN Haiyan1, WANG Xianen1   

  1. (1.Key Laboratory of Groundwater Resources and Environment,Ministry of Education,Jilin University,Changchun 130021,China; 2.Faculty of Management and Economics,Kunming University of Science and Technology,Kunming 650093,China
  • Online:2014-04-20

摘要:

能源消费总量控制是保障能源安全,积极应对气候变暖的重要手段;省域内能源消费量的合理分配,是落实国家能源消费总量控制的有效措施。提出能源消费总量分配应以公平为主、考虑区域发展权益的同时兼顾效率的原则,秉承“定基数,分增量”的思想,构建了基于信息熵的多因子混合加权分配模型,对目标年能源消费增量进行分配;选择了10个指标从经济水平、能耗水平、发展现状、产业结构及城市发展定位5个方面描述各地区的节能潜力及控制能耗量的责任,拟对能源消费总量在省内各市区的分配进行探索性研究。并以安徽省为例,对安徽省2015年能源消费总量分配到各市区进行了实证分析。结果显示,2015年安徽省17个市区能耗分配量增长率范围为1193%~5045%,能耗增幅的分配结果整体上受各市区人均GDP和人均能源消费量水平所支配,受单位工业增加值能耗和城市化率所调控

Abstract:

The total energy control is an important measure to ensure energy security and to respond to climate warming. The reasonable distribution of energy consumption within one province is an effective measure in order to implement the national energy consumption. In this paper, adhering to the idea of “given cardinality and divisible increment”, we built a multifactor mixedweighted distribution model based on information entropy to allocate energy consumption increment in the targetyear under the principle that focused on fair and also accounted for regional development interest and efficiency. Besides, we chose the indices of economic level, energy consumption level, industrial structure, etc. to describe the energysaving potential and the responsibility of energy consumption control. Taking Anhui Province as an example, we allocated energy consumption to each area in 2015. The results show that the energy growth rates of all 17 areas in Anhui province ranged from 1193% to 5045% in 2015. The distribution result is predominated by per capita GDP and per capita energy consumption level which are adjusted by the energy consumption of per industrial added value and urbanization rate

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