Hi Thomas,
- Deployment setup. I presume that the edge on which the predictor is enabled must have a Timedata provider (i.e a DB like InfluxDB) in place so that the input values can be stored. Is this correct?
I recommend Timedata.Rrd4j as local Timedata provider, as it works well with flash storage.
- How to incorporate additional variables in the prediction? I can see that in Apache Felix, the only parameter that the predictor takes is the ‘Channel-Address’ of the value to be predicted. Can the model use additional values that may be relevant?
I assume you would like to add weather or irradiation data this way. It’s not that simple unfortunately. The current LSTM predictor is designed to predict _sum/ConsumptionActivePower and _sum/UnmanagedConsumptionActivePower only. Prediction of _sum/ProductionActivePower will require a slightly adapted implementation.
For now I recommend using Predictor.PersistenceModel, as suggested here: Clarification about Genetic Algorithm and Time-of-Use Controller - #3 by stefan.feilmeier
- Where are predictions used and how can they be accessed by other controllers? If I want to control my ESS based on predictions, how can this be done?
Most prominent Controllers to use predictions are Controller.Ess.GridOptimizedCharge and Controller.Ess.Time-Of-Use-Tariff.
E.g to discharge a battery in the morning in expectation of significant PV generation.
This is something we consider for future and will require adjustment e.g. of the Time-Of-Use-Tariff-Controller and the cost function of the Optimizer. This behaviour is not allowed without external trader under German legislation at the moment, which makes it a lower priority for us…
Regards,
Stefan