Improving NILM by Combining Sensor Data and Linear Programming

Knowing the plug-level power consumption of each appliance in a building can lead to drastic savings in energy consumption. Non-Intrusive Load Monitoring (NILM) is a method for disaggregating power loads in a building to the single appliance level, without using direct sensors or electric meters attached to each device. This paper addresses the issues of NILM inaccuracy in the context of industrial or commercial buildings, by combining data from a low-cost, general-purpose, wireless sensor network. A novel approach to tackle this issue is proposed, using a simplex-based solver, to estimate the power load values of the steady states on sliding windows of data with varying size. In this paper, we show the principle of the approach and demonstrate its interest, limited complexity, and ease of use.