Nonintrusive identification of the energy consumption of individual loads from an aggregate power stream typically relies on relatively well-defined transient signatures. However, some loads have non-constant power demand that varies with loading conditions. These loads, such as computer-controlled machine tools, remain stubbornly resistant to conventional nonintrusive electrical monitoring methods. The power behavior of these loads can be modelled with stochastic processes. This paper presents statistical feature extraction techniques for identification of this fluctuating power behavior. An energy estimation procedure is presented and evaluated for two case studies: load operation on a shipboard microgrid and laboratory machine shop equipment.
