Comparative Electrical Load Prediction with Machine Learning and Fractional Calculus Applications

Forecasting short-term electrical loads is crucial for power supply system management, sustainability and upkeep. There are two main objectives for this study. First, it seeks to provide a thorough comparison of deep learning and machine learning techniques while forecasting for 1-h-ahead and 1-d-ahead. To remove any disruptions from the time series and comprehend its dynamics, the study also concentrates on mathematically modelling electricity load data using fractional calculus.