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Forecasting the primary energy consumption using a time delay grey model with fractional order accumulation

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  • Liang Zeng

Abstract

Energy consumption prediction is a hot issue, which is of great significance to regional energy security. In the existing prediction research with small samples, the time delay characteristic of an energy consumption system in itself is often ignored. To reflect the time delay characteristic of an energy consumption system and accurately grasp its development trend, a novel nonlinear time delay grey model with fractional order accumulation is presented. The new model is utilized to forecast and analyze Guangdong’s primary energy consumption, in which the time delay parameter is ascertained by the grey correlation analysis method, and the other parameters are determined via particle swarm optimization. The results show the simulation accuracy of the new model is higher than those of the other 3 grey models, and the predicted results in the next three years can provide decision-making and theoretical reference for the relevant departments of Guangdong province.

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  • Liang Zeng, 2021. "Forecasting the primary energy consumption using a time delay grey model with fractional order accumulation," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 27(1), pages 31-49, January.
    • Handle: RePEc:taf:nmcmxx:v:27:y:2021:i:1:p:31-49
    DOI: 10.1080/13873954.2020.1859547
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    Cited by:

    1. Michal Pavlicko & Mária Vojteková & Oľga Blažeková, 2022. "Forecasting of Electrical Energy Consumption in Slovakia," Mathematics, MDPI, vol. 10(4), pages 1-20, February.
    2. Huiping Wang & Yi Wang, 2022. "Estimating per Capita Primary Energy Consumption Using a Novel Fractional Gray Bernoulli Model," Sustainability, MDPI, vol. 14(4), pages 1-22, February.

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