Multi Situational Layer and Model Zoo

When building a model, TIM first tries to recognize all situations that might occur when using this model in production. A situation in this context is a combination of the time of forecasting, the forecasting horizon and the data availability. Usually, many different situations occur. TIM creates a separate model for each situation, optimized given the situation's conditions, and then combines all of these models into one Model Zoo. When TIM is asked to make a forecast, the current situation is automatically recognized and the most appropriate model is deployed.

This enables the creation of very simple models for straightforward situations - such as solar production at night, for example - and more complex models for more difficult situations. In other words, TIM is able to include necessary complexity in certain situations, while eliminating redundant complexity in other situations. As a lot of focus is put on TIM's fast forecasting capabilities, it is important that TIM can recognize how these situations differ from each other. TIM can intelligently exploit similarities between models during model building.

This optimization of all individual models is run by TIM's multi-situational layer.