Short-term Electric Load Forecasting using Engineering and Deep Learning techniques

Abstract

Load forecasting in the energy sector is an integral part of the electrical system as it is a criterion for its smooth and sustainable operation. The liberalization of electricity, the entry of RES into production and the digitization of supervisory means have brought more complexity to the system which translates into more variables. Machine learning models have the ability to process large numbers of parameters and this makes them attractive to researchers. In the context of this article, through the literature review, the prediction of electric load will be studied using artificial intelligence and specifically machine learning and deep learning which constitute the State of the Art in algorithms. © 2022 IEEE.