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A novel fractional discrete grey model with an adaptive structure and its application in electricity consumption prediction

Yitong Liu (College of Information Science and Engineering, Northeastern University, Shenyang, China)
Yang Yang (Bohai University, Jinzhou, China)
Dingyu Xue (College of Information Science and Engineering, Northeastern University, Shenyang, China)
Feng Pan (College of Information Science and Engineering, Northeastern University, Shenyang, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 3 August 2021

Issue publication date: 22 November 2022

139

Abstract

Purpose

Electricity consumption prediction has been an important topic for its significant impact on electric policies. Due to various uncertain factors, the growth trends of electricity consumption in different cases are variable. However, the traditional grey model is based on a fixed structure which sometimes cannot match the trend of raw data. Consequently, the predictive accuracy is variable as cases change. To improve the model's adaptability and forecasting ability, a novel fractional discrete grey model with variable structure is proposed in this paper.

Design/methodology/approach

The novel model can be regarded as a homogenous or non-homogenous exponent predicting model by changing the structure. And it selects the appropriate structure depending on the characteristics of raw data. The introduction of fractional accumulation enhances the predicting ability of the novel model. And the relative fractional order r is calculated by the numerical iterative algorithm which is simple but effective.

Findings

Two cases of power load and electricity consumption in Jiangsu and Fujian are applied to assess the predicting accuracy of the novel grey model. Four widely-used grey models, three classical statistical models and the multi-layer artificial neural network model are taken into comparison. The results demonstrate that the novel grey model performs well in all cases, and is superior to the comparative eight models.

Originality/value

A fractional-order discrete grey model with an adaptable structure is proposed to solve the conflict between traditional grey models' fixed structures and variable development trends of raw data. In applications, the novel model has satisfied adaptability and predicting accuracy.

Keywords

Acknowledgements

This work was supported by the National Natural Science Foundation of China [grant numbers 61174145, 61673094], and the Fundamental Research Funds for the Central Universities under Grants N2104029.

Citation

Liu, Y., Yang, Y., Xue, D. and Pan, F. (2022), "A novel fractional discrete grey model with an adaptive structure and its application in electricity consumption prediction", Kybernetes, Vol. 51 No. 10, pp. 3095-3120. https://doi.org/10.1108/K-04-2021-0257

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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