Identification of typical load profiles using K-means clustering algorithm | IEEE Conference Publication | IEEE Xplore

Identification of typical load profiles using K-means clustering algorithm


Abstract:

Typical load profile (TLP) describes the hourly values of electricity consumption on a daily basis, and is associated to a certain consumer category, for certain specific...Show More

Abstract:

Typical load profile (TLP) describes the hourly values of electricity consumption on a daily basis, and is associated to a certain consumer category, for certain specific operating conditions. TLPs can be defined for residential, small industrial, commercial or services consumers, for warm season and cold season, for week days and weekends. In this paper, the daily load curves of a residential feeder are grouped using K-Means clustering algorithm to classify the load curves. The paper further explores the relationship between load profiles and seasonal periods to identify season types. The paper also obtains truncated discrete Fourier transform coefficients for the load curves to reduce the dimensionality of the clustering problem. Application of K-Means clustering on the discrete Fourier coefficients exhibits results that are identical to the clusters of the original load curves.
Date of Conference: 04-05 November 2014
Date Added to IEEE Xplore: 05 March 2015
ISBN Information:
Conference Location: Nadi, Fiji

References

References is not available for this document.