Domestic Electrical Appliances Recognition from the
Knowledge of their Internal Components Consumption
European directive 2006/32/CE on energy efficiency enforces to furnish “sufficient” information to the consumer in
order to understand and allow him to reduce his electrical consumption. This can be done in several ways and one
partial solution is given by the currently installed numerical “smart” meters. However, the services offered by the
new meters are essentially electricity producer oriented with information allowing an easier billing (and cheapest
for the producer itself).
This solution is not optimized for customers. Nevertheless, it is possible to give really interesting information to the
customer to fulfill the European objective and by doing this increase the welfare. However, the useful information
to provide to the customer is not the easiest to obtain. Indeed, the customer is interested in answers to thos
complex questions: “Is my electrical consumption not too high?”, “Is all my electrical installation efficient
enough?”, “Can I change my habits (easily!!) for reducing my electrical consumption?”, etc. All those interrogations
are dependent on the consumer himself and require certain knowledge about the “house inside”. This can be
achieved by measuring perfectly every single electrical appliance in the house… Of course, this is not easy to accept
for residents in the house because it is really intrusive and difficult to implement.
The ideal solution from the point of view of the residents is to put a unique measurement point at the global
connection point of the house (the same place than the house meter) and get all the information on his electrical
consumption from that unique source of information. This is the NIALM (Non-Intrusive Appliance Load Monitoring)
concept. Of course this approach requires a lot more computational complexity to recover all the distributed
information in the house from that unique information.
The ECA (Energy Consumption Advisor) project launched by the BEAMS service attempts to implement the NIALM
concept. Hence, the idea consists in measuring the voltage and currents at the global connection point and, by
disaggregation algorithms, retrieve all the information contained in the global signals.
The system is partly implemented by a spin-off of the ULB and is currently evolving with new algorithms, hardware
implementation, data, etc.
In that general context, the general targets of this master thesis are:
To study the complex appliances (as exhaustively as possible): internal components, general working
principle, typical utilization, etc.
To complete current recognition algorithms in order to group components that compose a multicomponent appliance (for instance: washing machine = motor + heating resistance + valves + etc),
To identify and label the corresponding ensembles of components to the most probable known electrical
All this analysis can be conducted thanks to already available information in the implemented algorithms or with
some other external information. For instance, to group components, we can base the analysis on time but to label
one appliance, it can be useful to know the outside temperature (if it is summer and sunny, a heating resistance
corresponds more probably to an oven than a house heating system). Useful information is to define totally.