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Identification of typical load profiles using K-means clustering algorithm

conference contribution
posted on 22.10.2018, 00:00 by Salahuddin AzadSalahuddin Azad, ABMS Ali, Peter WolfsPeter Wolfs
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. © 2014 IEEE.

History

Start Page

158

End Page

163

Number of Pages

6

Start Date

04/11/2014

Finish Date

05/11/2014

ISBN-13

9781479919550

Location

Nadi, Fiji

Publisher

IEEE

Place of Publication

Piscataway, NJ.

Peer Reviewed

Yes

Open Access

No

Era Eligible

Yes

Name of Conference

Asia-Pacific World Congress on Computer Science and Engineering (2014)