  The growing penetration of variable renewable energy sources (VRES) requires
additional flexibility reserve to ensure reliable power system operations.
Current industry practice typically assumes a certain fraction of the VRES
power production forecast as flexibility reserve, thus ignoring other relevant
information, such as weather conditions. To address this, probability- and
risk-based reserve sizing models have been proposed, which use probabilistic
VRES power forecasts that mostly rely on historical forecast and actual VRES
power data for model training. Hence, these approaches are not suitable for
planned or newly installed wind farms, where no or insufficient historical data
is available. This paper addresses this caveat. First, we propose a
weather-driven probabilistic forecasting method for wind power installations
using publicly available weather data. Second, we apply the resulting
probabilistic forecasts to a novel risk-based flexibility reserve sizing model
that is compatible with the current reserve procuring pipeline used by US ISOs.
Finally, we compare the risk-based reserve requirements to industry practice,
state-of-the-art reserve procurement methods, and a weather-ignorant benchmark
with respect to system cost and security. Our results are obtained from
real-world data on a 1819-bus NYISO system model with both on- and projected
off-shore wind power installations, which highlight the usefulness of weather
information wind power forecasting and demonstrate efficiency gains from
risk-aware reserve procurement.
