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What is Currently Driving the Growth of China’s Household Electricity Consumption? A Clustering and Decomposition Analysis

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  • Ming Meng

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Shucheng Wu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Jin Zhou

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Xinfang Wang

    (School of Chemical Engineering, University of Birmingham, Edgbaston, B15 2TT Birmingham, UK)

Abstract

The rapid growth of household electricity consumption is threatening the sustainable development of China’s economy and environment because of its impacts on the operation efficiency of the electric power system. To recognize the driving factors of the consumption growth and offer policy implications, based on the consumption-related data of 2015 and 2016, this research used the rank sum ratio (RSR) method to divide China’s 30 provinces into 5 groups and a logarithmic mean Divisia index (LMDI) algorithm to decompose the composition growth of each group into the quantitative contribution of each driving factor. The following conclusions were drawn from the empirical analysis. (1) The Yangtze basin is the most vigorous region of consumption growth and should be principally monitored. (2) Climate conditions have a remarkable impact on consumption growth and should be a key consideration when making differentiated household electricity policies. (3) The rebound effect has already appeared in a few of the most developed regions. Electricity price is an effective measure in dealing with this effect. (4) The improvement of the income level is the most important driving factor for consumption growth. (5) For provinces with high growth vitality, the change in the burden level of electricity expenditure prompts consumption growth. However, for provinces with low growth vitality, the situations are opposite. (6) The impacts of electricity price and population on consumption growth are negligible.

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  • Ming Meng & Shucheng Wu & Jin Zhou & Xinfang Wang, 2019. "What is Currently Driving the Growth of China’s Household Electricity Consumption? A Clustering and Decomposition Analysis," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4648-:d:261152
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    References listed on IDEAS

    as
    1. Fu, Xin & Zeng, Xiao-Jun & Feng, Pengpeng & Cai, Xiuwen, 2018. "Clustering-based short-term load forecasting for residential electricity under the increasing-block pricing tariffs in China," Energy, Elsevier, vol. 165(PB), pages 76-89.
    2. Wang, Zhaohua & Lu, Milin & Wang, Jian-Cai, 2014. "Direct rebound effect on urban residential electricity use: An empirical study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 124-132.
    3. Dongxiao Niu & Si Li & Shuyu Dai, 2018. "Comprehensive Evaluation for Operating Efficiency of Electricity Retail Companies Based on the Improved TOPSIS Method and LSSVM Optimized by Modified Ant Colony Algorithm from the View of Sustainable ," Sustainability, MDPI, vol. 10(3), pages 1-26, March.
    4. Meng, Ming & Wang, Lixue & Shang, Wei, 2018. "Decomposition and forecasting analysis of China's household electricity consumption using three-dimensional decomposition and hybrid trend extrapolation models," Energy, Elsevier, vol. 165(PA), pages 143-152.
    5. He, Xiaoping & Reiner, David, 2016. "Electricity demand and basic needs: Empirical evidence from China's households," Energy Policy, Elsevier, vol. 90(C), pages 212-221.
    6. Lu Jiang & Xingpeng Chen & Bing Xue, 2019. "Features, Driving Forces and Transition of the Household Energy Consumption in China: A Review," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    7. Liu, Dan, 2017. "Evaluating the multi-period efficiency of East Asia airport companies," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 71-82.
    8. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    9. Cheng Li & Xiaojing Zhang, 2017. "Renminbi Internationalization in the New Normal: Progress, Determinants and Policy Discussions," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 25(2), pages 22-44, March.
    10. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
    11. Nie, Hongguang & Kemp, René, 2014. "Index decomposition analysis of residential energy consumption in China: 2002–2010," Applied Energy, Elsevier, vol. 121(C), pages 10-19.
    12. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    13. Xu, X.Y. & Ang, B.W., 2014. "Analysing residential energy consumption using index decomposition analysis," Applied Energy, Elsevier, vol. 113(C), pages 342-351.
    14. Hualong Yang & Xuefei Ma, 2019. "Uncovering CO 2 Emissions Patterns from China-Oriented International Maritime Transport: Decomposition and Decoupling Analysis," Sustainability, MDPI, vol. 11(10), pages 1-19, May.
    15. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Multilevel LMDI decomposition of changes in aggregate energy consumption. A cross country analysis in the EU-27," Energy Policy, Elsevier, vol. 68(C), pages 576-584.
    16. Zhang, Ming & Song, Yan & Li, Peng & Li, Huanan, 2016. "Study on affecting factors of residential energy consumption in urban and rural Jiangsu," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 330-337.
    17. Cheng, Shulei & Wu, Yinyin & Chen, Hua & Chen, Jiandong & Song, Malin & Hou, Wenxuan, 2019. "Determinants of changes in electricity generation intensity among different power sectors," Energy Policy, Elsevier, vol. 130(C), pages 389-408.
    18. Khanna, Nina Zheng & Guo, Jin & Zheng, Xinye, 2016. "Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey," Energy Policy, Elsevier, vol. 95(C), pages 113-125.
    19. Berkhout, Peter H. G. & Muskens, Jos C. & W. Velthuijsen, Jan, 2000. "Defining the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 425-432, June.
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