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

Author

Listed:
  • Khodabaccus Noorshanaaz
  • Aslam Aly El-Faidal Saib

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.

Suggested Citation

  • Khodabaccus Noorshanaaz & Aslam Aly El-Faidal Saib, 2025. "Energy demand forecasting using a novel optimised Fourier grey Markov-based approach," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 53(1), pages 118-134.
    • Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:118-134
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