An order-specific clustering algorithm for the determination of representative demand curves

Data clustering consists of a group of procedures used to collect similar entries or data points within a set into clusters. No existing clustering echnique considers entries sequentially in time. In some cases, it is desirable to generate clusters that represent a segment of a time-ordered data et. For these purposes, an order-specific clustering algorithm is proposed. The proposed algorithm employs representative load curves to describe he clusters it generates. The capabilities of the order-specific clustering algorithm are demonstrated on a case study using electricity demand data or the province of Ontario, Canada. Two different applications of the clustering algorithm on this data set are given to demonstrate the effect of rror threshold values on the formation of clusters. An analysis of the error for each of these clustering applications is presented.