Load identification and management framework for private households

This paper describes a framework for the identification of household appliances based on a measured aggregated load profile. Device activation and deactivation events are detected by a set of non-intrusive algorithms collected in the software structure. These detections are then matched to a database of load values. The result which is basically a detection probability in combination with consumption data of the device, is displayed to the customer as energy feedback. This motivates users to apply energy-saving measures, or in combination with an home automation system appliances can be turned off automatically. Another concept is to implement more intelligence directly into the devices. Such smart appliances communicate with an energy management gateway and plan their activation autonomous. For the proof of concept a simulator for smart home appliances was developed and integrated into a demonstration setup. Finally the discussed results suggest that disaggregated energy feedback in combination with smart home appliances is a feasible approach in order to using the available energy in a more efficient way.