The document discusses improvements that can be made to production changes using short-term forecasting techniques. It notes typical improvements of 25% for the worst events in the next tradeable hour using LiDAR detection, 13% over the first 20 minutes using state-of-the-art machine learning on high frequency data, and 2-5% over an hour and 5-10% over 20 minutes from a high accuracy forecast setup combining multiple numerical weather prediction models.

1. STN- Improve in
Production Changes
1. 2. 3.
Typical improvements:
• 25% for top 8% worst
events for next tradeable
hour
Use LiDAR to detect
more
Typical improvements:
• 13% over the first 20
minutes
Improving short-term forecasts
+
0. State of the art machine learned, weighted, multi-model and persisted short-term
forecasts
+
High frequency data
for short term
algorithms
Typical improvements:
• 2-5% over an hour, and approx.
5-10% over the first 20
minutes
+
HIGH accuracy
forecast setup
4, 5, 6 NWP’s
or more… x