The Fuzzy Integrated Energy Prior-warning Model Based on Entropy Weight

The Fuzzy Integrated Energy Prior-warning Model Based on Entropy Weight

Yaqun He (China University of Mining and Technology, China), Hua Wei (China University of Mining and Technology, China), Weiran Zuo (China University of Mining and Technology, China), Xiaobing Wu (China University of Mining and Technology, China), Xin Ge (China University of Mining and Technology, China), Shan Wu (China University of Mining and Technology, China) and Baofeng Wen (China University of Mining and Technology, China)
DOI: 10.4018/978-1-60960-064-8.ch026
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Based on the analysis of five factors affecting energy risks, including supply and demand, economy, environment, transport, and disaster, this chapter establishes the prior-warning index system of the energy risk by covering 3 sub-systems and 37 indexes. The three sub-systems are the coal sub-system, the petroleum and natural gas sub-system, and the integrated factors sub-system. Fuzzy synthesis evaluation was applied to confirm the internal estimated index weight of the sub-systems. Moreover, the risk prior-warning model of the energy sub-systems was established by the method. The weights of the three sub-systems were determined through the concept of entropy weight, and the prior-warning indexes of energy risk were applied to evaluate the total energy security of the three sub-systems. Finally, the prior-warning model of energy risk in China was established. The entire situation of energy safety of China was summarized via empirical analysis.
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Energy is one of the material basis for human society evolution, as well as an important resource for the economic development and social improvement. The energy economic issue has been studied by a number of specialists from different point of views. These studies are mostly involved in the relationship of the energy consumption and affecting factors, the forecast of energy supply and demand, the energy security strategy and so on. A series of achievements have been made.

Goto (1995) and Richels & Sturm (1996) had studied the influence of greenhouse gas emission and control as well as its impact to economy, energy, and environment. Huntington & Brown (2002) established the relational models of energy and climate to study how to increase energy security by adjusting the energy consumption structure. Wang & Chen (1996) proposed the design principles and the basic framework of establishing the coal prior-warning systems and early warning index system. Wu (2002) put forward the security evaluation index system of petroleum resources, which included eight indexes. Wang (2002) established a resource security assessment system, which contained 14 indexes, based on the analysis of five key factors affecting resource security and conducted a preliminary assessment on China's petroleum and food security situation.

The above-mentioned studies have built a foundation to the energy prior-warning system. But the existing evaluation systems are still mainly qualitative. Even when they adopt empirical analysis, the research in general lacks comprehensiveness and systemization. In this chapter, 37 prior-warning indexes which covered coal, petroleum and natural gas, and integrated energy economy sub-systems were selected to establish the prior-warning model of China’s energy risk by applying fuzzy synthesis evaluation based on entropy weight. The empirical analysis of the results was made.


The Selection Of Prior-Warning Indexes

Energy security is influenced by many interrelated factors and their combined effects. In general, there are mainly five influencing factors. In view of the important role of coal, petroleum and natural gas in our domestic primary energy structure, the prior-warning research of the entire energy system, which is composed of coal sub-system, petroleum and natural gas sub-system, integrated sub-system, was researched extensively.

The integrated sub-system is not just a simple addition of each sub-system. The system mainly focuses on the analysis of comprehensive indexes, including primary energy supply and demand, energy consumption elasticity, unit Gross Domestic Product (GDP) energy consumption and so on. Considering that the new energy takes up a smaller proportion of the energy consumption, it is not considered as a sub-system, but only reflected in the integrated sub-system. The selection principles of energy prior-warning indexes are based on science, comprehensiveness, comparability, dynamic, sensitivity and availability. The prior-warning indexes’ Matrix of the energy risk is shown in Table 1.

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