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Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

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  • Jinchao Li

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China)

  • Lin Chen

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yuwei Xiang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Jinying Li

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

  • Dong Peng

    (State Power Economic Research Institute China State Grid Corp, Beijing 102209, China)

Abstract

Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.

Suggested Citation

  • Jinchao Li & Lin Chen & Yuwei Xiang & Jinying Li & Dong Peng, 2018. "Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:1:p:256-:d:127788
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    References listed on IDEAS

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    1. Mingyu Li & Dongxiao Niu & Zhengsen Ji & Xiwen Cui & Lijie Sun, 2021. "Forecast Research on Multidimensional Influencing Factors of Global Offshore Wind Power Investment Based on Random Forest and Elastic Net," Sustainability, MDPI, vol. 13(21), pages 1-19, November.
    2. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
    3. Suqi Zhang & Ningjing Zhang & Ziqi Zhang & Ying Chen, 2022. "Electric Power Load Forecasting Method Based on a Support Vector Machine Optimized by the Improved Seagull Optimization Algorithm," Energies, MDPI, vol. 15(23), pages 1-17, December.
    4. Xie, Minghua & Yi, Xiangyu & Liu, Kui & Sun, Chuanwang & Kong, Qingbao, 2023. "How much natural gas does China need: An empirical study from the perspective of energy transition," Energy, Elsevier, vol. 266(C).

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