A Brief Review of Energy Consumption Forecasting Using Machine Learning Models
Zahra Eddaoudi, Zineb Aarab, Khadija Boudmen, Asmae El Ghazi, Moulay Driss Rahmani
Abstract
Energy consumption forecasting plays a pivotal role in modern resource management and sustainable development. This paper presents a concise overview of state-of-the-art techniques and methodologies employed in the field of energy consumption forecasting, with a particular emphasis on the application of Machine Learning (ML) models. The paper surveys recent advancements, addresses key challenges, and identifies promising directions for future research in this critical domain. By examining the current landscape of energy consumption forecasting through the lens of machine learning, this review aims to offer researchers and practitioners valuable insights and guidance for enhancing the accuracy and efficiency of energy consumption pattern prediction.