Energy Analytics - Opportunities for Energy Monitoring and Prediction with smart Meters
By 2019, Norway will complete the national rollout of advanced metering systems (AMS) for all customers. Beyond near-time monitoring of voltage quality and frictionless billing of customers, such a rollout opens a host of possibilities. However, a full-scale rollout is not without challenges. For in...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | By 2019, Norway will complete the national rollout of advanced metering systems (AMS) for all customers. Beyond near-time monitoring of voltage quality and frictionless billing of customers, such a rollout opens a host of possibilities. However, a full-scale rollout is not without challenges. For instance, throughput limitations of radio-mesh networks, privacy considerations, and bounds on compute and Storage infrastructure limit the cardinality of metering data to levels below that of which established techniques(for example non-intrusive load disaggregation) require. Pilot projects are now exploring how to mitigate these challenges as well as seeking novel opportunities that open up through data fusion and recent advances in machine learning. In this contribution, we outline the capabilities of the Norwegian AMS system and describe established use-cases and non-intrusive load monitoring. We then discuss a pilot on detection of electric vehicles. Based on preliminary findings, we map the path forward. |
---|