-
Notifications
You must be signed in to change notification settings - Fork 0
FlexDR Documentation
Welcome to the FlexDR backend wiki!
This section aims to provide details of the FlexDR backend implementation focusing on the business perspective of the service.
Meters refer to the smart meters involved in the energy community. These smart meters along with their details could be easily registered via the FlexDR UI.
ML model refers to the clustering algorithm used to detect the load profiles of the smart meters involved in the energy community within I-NERGY UC7.
ML models contain all the information regarding the algorithm and its configuration used for clustering (e.g. kmeans, 14 clusters, euclidean distance) \ as well as the identified clusters in form of load curves. The ML model is tracked within I-NERGY MLflow instance, and is deployed as a service. \ ML model is registered via the API within FlexDR backend and MongoDB instance.
The concept behind a load profile is to group together multiple clusters identified by the ML model. If similarities exist between these profiles, Energy Experts, based on their expertise, can simplify and merge the clusters for better management and analysis. Load profile profile is created via the FlexDR UI and is linked with an existing ML model. It contains user defined attributes, such as description and a relevant recommendation, and a single or multiple clusters which is/are a subset of the clusters of the ML model.
Assignments: They will be created by a scheduled job and refers to the assignment of a cluster profile to a smart meter
for the day ahead based on the forecasted load.