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Factors influencing China’s non-residential power consumption: Estimation using the Kaya–LMDI methods

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  • Jiang, Shan
  • Zhu, Yongnan
  • He, Guohua
  • Wang, Qingming
  • Lu, Yajing

Abstract

Electric power plays an important role in the economic development of a nation and in improving human life. Since China is the world’s largest electricity consumer, an understanding of the factors influencing the growth in the consumption of electricity would help Chinese leaders design appropriate energy savings strategies and economic policies. Using the Logarithmic Mean Divisia Index (LMDI) method based on the Kaya identity, this study takes China’s non-residential power consumption from 2007 to 2016 as its research subject and decomposes the influencing factors into population size, economic development, regional economic structure, regional industrial structure, and electricity consumption intensity. We find that economic growth is the main factor influencing the growth of non-residential power consumption, mostly in the eastern region; moreover, the increased intensity of power consumption inhibits the growth of non-residential power consumption, with the suppression effect being more significant in the secondary industry. Population growth plays a small role in promoting electricity consumption. Regional economic structure has a negative effect on power consumption, showing a significant difference between provinces. From these results, regional differences and industrial structure are factors to be considered for the development and management of electricity. Therefore, technological innovation and management need to be strengthened, with focus on industrial structure adjustment and promotion of energy conservation technology in the central and western regions.

Suggested Citation

  • Jiang, Shan & Zhu, Yongnan & He, Guohua & Wang, Qingming & Lu, Yajing, 2020. "Factors influencing China’s non-residential power consumption: Estimation using the Kaya–LMDI methods," Energy, Elsevier, vol. 201(C).
  • Handle: RePEc:eee:energy:v:201:y:2020:i:c:s0360544220308264
    DOI: 10.1016/j.energy.2020.117719
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