Artificial Intelligence, Machine Learning and Optimization Models Applied to Wind Energy Forecasting: A Systematic Review of the Literature

This work presents a systematic literature review that analyzes the use of Artificial Intelligence, Machine Learning and optimization techniques in wind energy forecasting. Using the PRISMA and Methodi Ordinatio protocols, the most relevant articles from the last decade were selected. The results show the predominance of hybrid approaches, frequent use of neural networks and evolutionary algorithms, and a focus on meteorological variables. The bibliometric analysis indicates growing interest in the topic and international collaborations. The study provides a basis for the development of more effective and applicable models for wind power generation.