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An Improved MGM (1, n) Model for Predicting Urban Electricity Consumption

Author

Listed:
  • Zhenhua Li

    (School of Economics and Management, North University of China, Taiyuan 030051, China)

  • Jinghua Lu

    (Academic Affairs Office, North University of China, Taiyuan 030051, China)

Abstract

The MGM (1, n) model has the characteristics of less data required, simple modeling, and high prediction accuracy. It has been successfully applied to short-term forecasting across various economic, social, and technological domains, yielding promising outcomes. There is insufficient attention paid to the interpolation coefficient of the model. The interpolation coefficients determine the extent of model fitting, which, in turn, impacts its prediction accuracy. This study made some improvements to the interpolation coefficients and proposed an improved MGM (1, n) model. IMGM (1, n) model and MGM (1, n) model were employed to compare the performance of the improved MGM (1, n) model. Upon a series of comparisons and analyses, it was concluded that the improved MGM (1, n) model has higher fitting and prediction accuracy than the other two forecasting methods. The method was used to forecast the short-term electricity consumption of Linfen City. The findings revealed that by 2030, the electricity demand in Linfen City is projected to be 563.7 billion kWh.

Suggested Citation

  • Zhenhua Li & Jinghua Lu, 2024. "An Improved MGM (1, n) Model for Predicting Urban Electricity Consumption," Energies, MDPI, vol. 17(16), pages 1-12, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:16:p:3872-:d:1450872
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    References listed on IDEAS

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    1. Zheng-Xin Wang, 2015. "A Predictive Analysis of Clean Energy Consumption, Economic Growth and Environmental Regulation in China Using an Optimized Grey Dynamic Model," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 437-453, October.
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