%0 Journal Article
%T A Hybrid Mathematical Framework for Synthetic Energy Data Generation in Morocco Smart Grids
%A Rim Marah
%A Rania Marah
%A Abdelghani Chehayebat
%J Open Access Library Journal
%V 13
%N 7
%P 1-13
%@ 2333-9721
%D 2026
%I Open Access Library
%R 10.4236/oalib.1115538
%X 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.
%K Smart Grids
%K Energy Forecasting
%K Synthetic Data Generation
%K Time Series Modeling
%K Load Prediction
%K Climate Modeling
%K Socio-Cultural Energy Consumption
%K Ramadan Effect
%K Hybrid Mathematical Model
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=152727