Journal
CHAOS SOLITONS & FRACTALS
Volume 141, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2020.110429
Keywords
Electricity consumption; FPGM(1,1,t(alpha)); Metabolic mechanism; Quantum genetic algorithm (QGA)
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Funding
- Fundamental Research Funds for the Central Universities of China [2019YBZZ062]
- Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX20_1144]
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As one of the most important energy sources, electricity plays an important role in power system and is the main driving force for the development of the country and society. Accurately forecasting electricity consumption is of significance of the power system and market. For this, a novel fractional grey polynomial model with time power term (denoted as F PGM(1, 1, t(alpha))) is developed for forecasting electricity consumption of India and China, in which the grey polynomial model is optimized by combining time power term and fractional accumulation, the quantum genetic algorithm (QGA) is then applied to determine the model parameters. Particularly, the proposed model can be changed to other existing models by adjusting systematic coefficient. The numerical results shows that the proposed model outperforms other competitive models. Given the efficacy of the proposed model, it is applied to predict electricity consumption in the coming years, which could provide with a reference in preparing energy policies and strategies. (C) 2020 Elsevier Ltd. All rights reserved.
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