The rapid growth of wind and solar generation has introduced significant variability and uncertainty into the operation of electric power systems (SEP), challenging traditional methods for sizing operating reserves. This article presents a dynamic probabilistic method based on the convolution of probability distribution functions, aimed at accurately estimating the reserve required for Secondary Frequency Regulation (RSF) in contexts with high penetration of intermittent renewable sources. The proposed approach employs historical time series data with halfhour resolution for electricity demand, wind generation, and solar generation, applying a discrete convolution technique to combine their respectiveprobability distributions. Unlike conventional methods, this methodology allows for differentiated reserve estimation according to the hour of the dayand the type of day (weekday or non-week...