The research aims at improving the efficiency of energy use in commercial buildings by providing fine grained accounts on where electricity is spent. It can be implemented easily and fits within a new context: trying to find innovative solutions to apply load monitoring techniques in real-world environments.
The research has shown that the power contribution of individual appliances can be extracted from a building's power load captured with a single meter, via intelligent pattern recognition technique, or via combination with other sources of information such, as machines' activity onto local area networks indicating power consumers at a given time. Anthony Schoofs’ work has been implemented and tested into multiple pilot sites, ranging from hotels to hospitals, and is in the process of commercialisation.
Decomposing electricity spending down to equipment level enables quick discovery of equipment misuse, equipment faults, and most importantly equipment associated cost. In addition to high accuracy in decomposing electricity bills per appliance, primary requirements driving the research are scalability, non-intrusiveness, automation and low-cost, in order to address real-world deployments comprising tens to hundreds of appliances operating concurrently within a building.