Non-intrusive appliance load identification using cascaded cognitive learning

A method for identifying energy consumption associated with at least one appliance comprising:

• measuring an energy consumption signal;
• obtaining publicly available information of a location of the at least one appliance;
• estimating a plurality of probabilities of energized appliances based on the energy consumption signal and the publicly available information;
• generating a new combination of the estimated plurality of probabilities of energized appliances;
• and
• decomposing the at least one energy consumption signal into constituent individual loads and corresponding energy consumption.

An energy measurement system comprising:

• at least one sensor configured to measure at least one output signal associated with a plurality of appliances;
• a communication interface configured to transmit the at least one output signal to a remote utility station;
• an orientation module configured to gather publicly available information associated with a location of the appliances;
• a planning module configured to generate an appliance database based on an input signal from the orientation module;
• a decomposition module configured to decompose the at least one output signal into constituent individual loads and therefrom identify energy consumption corresponding to each appliance based on the appliance database;
• wherein the orientation module, the planning module and the decomposition module are located at the remote utility station.