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Rinaldi, A., Schweiker, M. and Iannone, F. (2018) On Uses of Energy in Buildings: Extracting Influencing Factors of Occupant Behaviour by Means of a Questionnaire Survey. Energy and Buildings, 168, 298-308.
https://doi.org/10.1016/j.enbuild.2018.03.045

has been cited by the following article:

• TITLE: A Hybrid Mathematical Framework for Synthetic Energy Data Generation in Morocco Smart Grids

  AUTHORS: Rim Marah, Rania Marah, Abdelghani Chehayebat

  KEYWORDS: Smart Grids, Energy Forecasting, Synthetic Data Generation, Time Series Modeling, Load Prediction, Climate Modeling, Socio-Cultural Energy Consumption, Ramadan Effect, Hybrid Mathematical Model

  JOURNAL NAME: Open Access Library Journal, Vol.13 No.7, July 23, 2026

  ABSTRACT: The development of accurate energy forecasting models for smart grids is strongly dependent on the availability of high-quality and high-resolution datasets. However, in many developing regions, particularly in Morocco, such datasets remain scarce, incomplete, or non-public. This limitation significantly constrains the application of advanced machine learning and deep learning techniques for energy demand prediction and grid optimization. This paper proposes a novel hybrid synthetic energy data generation framework specifically designed for the Moroccan context. The proposed approach integrates temporal dynamics, climatic influences, and socio-cultural behavior into a unified mathematical model for hourly electricity consumption simulation. In particular, the model explicitly incorporates seasonal variations, temperature-dependent effects, and behavioral shifts induced by socio-cultural events, including Ramadan and weekend patterns.