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A Novel Extrapolation-Based Grey Prediction Model for Forecasting China’s Total Electricity Consumption

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  • Xin-bo Yang

Abstract

Accurately forecasting China’s total electricity consumption is of great significance for the government in formulating sustainable economic development policies, especially, China as the largest total electricity consumption country in the world. The calculation method of the background value of the GM(1, 1) model is an important factor of unstable model performance. In this paper, an extrapolation method with variable weights was used for calculating the background value to eliminate the influence of the extreme values on the performance of the GM(1, 1) model, and the novel extrapolation-based grey prediction model called NEGM(1, 1) was proposed and optimized. The NEGM(1, 1) model was then used to simulate the total electricity consumption in China and found to outperform other grey models. Finally, the total electricity consumption of China from 2018 to 2025 was forecasted. The results show that China’s total electricity consumption will be expected to increase slightly, but the total is still very large. For this, some corresponding recommendations to ensure the effective supply of electricity in China are suggested.

Suggested Citation

  • Xin-bo Yang, 2021. "A Novel Extrapolation-Based Grey Prediction Model for Forecasting China’s Total Electricity Consumption," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, June.
  • Handle: RePEc:hin:jnlmpe:5576830
    DOI: 10.1155/2021/5576830
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    Cited by:

    1. Zizhen Cheng & Li Wang & Yumeng Yang, 2023. "A Hybrid Feature Pyramid CNN-LSTM Model with Seasonal Inflection Month Correction for Medium- and Long-Term Power Load Forecasting," Energies, MDPI, vol. 16(7), pages 1-18, March.

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