Calculating energy loss during an outage

A non-transitory computer-readable medium storing instructions, that when executed by at least one processor, cause the at least one processor to:

• receive historical meteorological windspeed data associated with a site location of an energy generating device collected during a previous time duration;
• receive historical device windspeed data measured at the energy generating device during the previous time duration;
• train, using a machine learning algorithm, a neural network using at least a portion of the historical meteorological windspeed data and the historical device windspeed data;
• receive an alert indicating that windspeed data indicating device windspeeds measured at the energy generating device are unavailable within a particular time duration;
• receive meteorological data associated with the site location of the energy generating device, the meteorological data including meteorological windspeed data collected within the particular time duration;
• and
• predict one or more estimated device windspeeds at the energy generating device during the particular time duration based on the meteorological data using the neural network for the energy generating device.

An apparatus, comprising:

• at least one processor;
• and
• at least one memory, the at least one memory storing instructions, that when executed by the at least one processor, cause the at least one processor to:
• receive historical meteorological windspeed data associated with a site location of an energy generating device collected during a previous time duration;
• receive historical device windspeed data measured at the energy generating device during the previous time duration;
• train, using a machine learning algorithm, a neural network using at least a portion of the historical meteorological windspeed data and the historical device windspeed data;
• receive an alert indicating that windspeed data indicating device windspeeds measured at the energy generating device are unavailable within a particular time duration;
• receive meteorological data associated with the site location of the energy generating device, the meteorological data including meteorological windspeed data collected within the particular time duration;
• and
• predict one or more estimated device windspeeds at the energy generating device during the particular time duration based on the meteorological data using the neural network for the energy generating device.