The integration of wind energy into power systems has intensified as a result of the urgency
for global energy transition. This requires more accurate forecasting techniques that can capture
the variability of the wind resource to achieve better operative performance of power systems. This
paper presents an exhaustive review of the state-of-the-art of wind-speed and -power forecasting
models for wind turbines located in different segments of power systems, i.e., in large wind farms,
distributed generation, microgrids, and micro-wind turbines installed in residences and buildings.
This review covers forecasting models based on statistical and physical, artificial intelligence, and
hybrid methods, with deterministic or probabilistic approaches. The literature review is carried out
through a bibliometric analysis using VOSviewer and Pajek software. A discussion of the results is
carried out, taking as the main approach the forecast time horizon of the models to identify their
applications. The trends indicate a predominance of hybrid forecast models for the analysis of power
systems, especially for those with high penetration of wind power. Finally, it is determined that most
of the papers analyzed belong to the very short-term horizon, which indicates that the interest of
researchers is in this time horizon.