IDENTIFICATION OF ALTERNATIVE RENEWAL ELECTRIC-LOAD MODELS FROM ENERGY MEASUREMENTS

In statistical load modeling methodologies, aggregate electric load be havior is derived by propagating the ensemble statistics of an individ ual load process which is representative of the loads in the aggregate . Such a modeling philosophy tends to yield modets whereby if physical meaning is present at the elemental level, it is preserved at the agg regate level. This property is essential for applications involving di rect control of power system loads (for peak load shaving purposes, fo r example). The potential applicability of statistical load models is a strong function of one's ability to limit the volume of unusual data required to build those. An identification algorithm for a previously proposed stochastic hybrid-state Markov model of individual heating-c ooling loads is presented. It relies only on data routinely gathered i n power systems (device energy consumption over constant time interval s). It exploits an alternating renewal viewpoint of the load dynamics. After deriving some general results on the occupation statistics of t ime homogeneous alternating renewal processes, the analysis is focused on the specific model. In the process, however, some intriguing featu res likely to be shared by a wide class of alternating renewal process es are revealed.