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The energy efficiency model under the market response and the evolutionary path under its regulation policy in China

  • Guangyong Zhang
  • Lixin Tian
  • Wenbin Zhang
  • Xu Yan
  • Bingyue Wan
Original Article
  • 45 Downloads

Abstract

According to the causal relationship among energy efficiency, energy price, and economic growth in China, a network structure of mutual transmission is constructed and a novel model of nonlinear dynamic system is also established. With the help of numerical simulation, the impacts of the parameters on the motion state of the system and the subsystem are analyzed. Then, the parameters are identified by means of BP neural network, and the model of novel dynamic system is given, which has a practical significance to reflect the actual situation of the system in China. According to the state of the actual evolution, we analyze the regulatory effect of the policy on the state of the system and find that four policies can all make the unstable system become stable. Comparing and analyzing the regulatory effects of the single and combined policy on the system show that the combined policy has a shorter time to reach the stable state and it is more conducive to the reduction of energy price. However, the single policy has a better effect on improving the level of energy efficiency and economic growth. In addition, the evolutionary paths of energy efficiency are analyzed at different regulatory levels under the same policy, and the results show that the higher the regulatory level is and the shorter time it takes to reach steady state for energy efficiency, the lower the level of energy efficiency is.

Keywords

Energy efficiency Energy price Economic growth Numerical simulation Regulatory policy 

Notes

Funding

This research is supported by grants from the National Natural Science Foundation of China (No: 71690242, 91546118, 11731014) and Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_2256).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Nonlinear Scientific Research Center, Faculty of ScienceJiangsu UniversityZhenjiangPeople’s Republic of China
  2. 2.Energy Interdependence Behavior and Strategy Research Center, School of Mathematical SciencesNanjing Normal UniversityNanjingPeople’s Republic of China
  3. 3.School of Mathematical Science, Taizhou Institute of Sci. & TechNUSTTaizhouPeople’s Republic of China

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