Section: New Results
Participants : Nicolas Roux, Olivier Sentieys.
Developing smarter and greener buildings has been an expanding field of research over the last decades. One of the essential requirements for energy utilities is the knowledge of power consumption patterns at the single-appliance level. To estimate these patterns without using an individual power meter for each appliance, Non-Intrusive Load Monitoring (NILM) consists in disaggregating electrical loads by examining the appliance specific power consumption signature within the aggregated load single measurement. Therefore, the method is considered non-intrusive since the data are collected from a single electrical panel outside of the monitored building. Thus, NILM has been a very active field of research with renewed interest over the last years.
Therefore, knowing the plug-level power consumption of each appliance in a building can lead to drastic savings in energy consumption. In , we have addressed the issue of NILM inaccuracy in the context of industrial or commercial buildings, by combining data from a low-cost, general-purpose, wireless sensor network. We have proposed a novel approach based on a simplex solver to estimate the power load values of the steady states on sliding windows of data with varying size. We have shown the principle of the approach and demonstrated its interest, limited complexity, and ease of use.