How to improve your energy forecasts by using multiple AI/ML models

There are many different forecasting system suppliers, many weather suppliers and a lot of new AI/ML models that can be used for different kinds of forecasts.

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Some of the forecasting models performs better for wind power forecasts, some for PV forecasts and some performs best at a specific situation, for example at high wind speeds. The challenge is to know which suppliers to use or which combination of suppliers to use to choose to get the best forecast accuracy compared to the cost of the suppliers.

The 10th of May we will arrange a webinar where we will present how to make evaluations of external suppliers, such as: 
- Weather suppliers
- Forecasting system suppliers
- Internal/external forecasting models

We will also show you how you can use a combination of external suppliers as input to our AI/ML models to get the best out of your forecasts. And the best of all, how easy it is to set up and arrange these kinds of evaluations.

Part 2
A general presentation of Aiolos Forecast Studio Some and some examples of what we will present are:

- Indata Control, our intelligent warning system to find and correct bad historical data in an automated way
- How can Aiolos by itself choose which models or which combination of models to use in different situations.
- How we are using several AI/ML models to improve the forecasts
- How to use regimes in Aiolos to improve the forecasts
There will also be time for questions and discussions at the webinar. The webinar is free of charge, and you are more than welcome to also invite colleagues if you would like.
The webinar is free of charge. 

When - 10 of May 2024 at 14.00 CET
Where - Online – Teams
How to sign on? 
Questions - Contact Kristoffer Roger, +46 70 300 2546