  Sizing frequency control ancillary service (FCAS) requirements is crucial for
the reliable operation of power systems amid a continuous influx of variable
renewable energy (VRE) generation. Reserve sizing is especially pertinent for
the Philippine grids due to an expected transition to new FCAS classifications
established by its Grid Code. In lieu of the existing deterministic
formulation, this work proposes a dynamic approach for sizing secondary and
tertiary reserves that accounts for the stochasticity and variability of load
demand and VRE. We propose a method where historical power imbalances were
calculated and clustered according to the time and day of week they occurred.
The conditional probabilities of forecast and noise errors were characterized
using kernel density estimation. Recursive convolution was performed to obtain
the total reserve requirement probability distribution. The method was tested
on Visayas grid's historical system operation data and used target reliability
levels on the error distributions to size upward and downward reserve needs.
Finally, the methodology was extended to demonstrate through a numerical
experiment that sizing FCAS at temporal resolutions higher than one-hour, e.g.,
five-minute, provides the benefit of shrinking the required capacities by as
much as 86.2\% compared to current deterministic FCAS sizing.
