Skip to Main Content
The new emerged operating conditions in the power sector are forcing the power-market participants to develop new tools. Among them, load profiles are a key issue in retail power markets. For various types of small consumers without quarter-hourly load measurements, determination of typical load profiles (TLPs) could serve as a tool for determining of their load diagrams. Their main function is in billing of consumers who have deviated from their contracted schedules. Moreover, a simple and straightforward method for assigning a TLP to a particular eligible consumer also needs to be established. In this paper, a methodology for allocating consumers' load profiles using probabilistic neural network (PNN) is presented. It is based on the preprocessed measured load profiles (MLPs), using wavelet multiresolution analysis, clustered with a FCM clustering algorithm with an appropriate cluster-validity measure. The results demonstrate the efficiency of the formation procedure for the proposed TLPs.