NONINTRUSIVE IDENTIFICATION OF RESIDENTIAL CUSTOMERS

We present a new approach which identifies the number of customers wit hin particular categories living in a chosen area of energy supply. Th is identification is made from total energy consumption measured at di stribution feeders by applying characteristic patterns of energy use a nd nonlinear programming techniques. Customers were segmented into fou r main categories with six sub-groups in each category. A total patter n of energy use was obtained by summing for each sub-group the energy consumption which is based on the characteristic patterns of energy us e for that sub-group and the number of customers in that sub-group. Si mulations were carried out to verify different optimization procedures . Results show that a variable matrix optimization procedure can ident ify customers most accurately by minimizing the assumed objective func tion to a negligible value after 100 iterations. (C) 1997 Elsevier Sci ence Ltd.