Impacts of temporal resolution exploitation hand-picked bunch ways on residential electricity load profiles

This paper presents an application of support vector clustering (SVC) to electrical load classification. The SVC approach includes Gaussian kernel and clustering algorithm to exploit the location of the bounded support vectors (BSVs) to define the outliers, identifying the clusters in function of the distance of the non-BSVs to the BSVs. Its implementation is comparatively less computational behavior and the single user defined threshold is used. Extended comparison to other clustering methods is included to show the effectiveness of the proposed approach in grouping multidimensional load pattern data into non-overlapping clusters. The successive task is to identify the outliers and clustering few details.