Energy demand forecasting using a novel optimised Fourier grey Markov-based approach

Khodabaccus Noorshanaaz and Aslam Aly El-Faidal Saib

International Journal of Operational Research, 2025, vol. 53, issue 1, 118-134

Abstract: Energy supply affects the sustainable development of an economy, hence making its modelling and forecasting crucial to policymakers. Conventional statistical models often require either prior assumptions on the distribution of the data or large historical datasets. This paper proposes the optimised Fourier-Markov grey model (OFGM), which alleviates the former two assumptions. Two test scenarios are proposed for assessing the model's performance: data prior to the COVID-19 pandemic (2010-2019) and data extending over the pandemic period (2010-2020). Numerical experiments demonstrate that the proposed algorithm very well models both scenarios and a significant improvement in the prediction accuracy is achieved.

Keywords: grey prediction model; Fourier; Markov; metaheuristic algorithm; energy forecasting. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:53:y:2025:i:1:p:118-134

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