On the use of information theoretic mean shift for electricity load patterns clustering

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Sumaili, J (Author) Other; Keko, H (Author) Other; Vladimiro Miranda (Author) FEUP; Chicco, G (Author) Other

Conference proceedings International

Title: 2011 IEEE PES Trondheim PowerTech: The Power of Technology for a Sustainable Society, POWERTECH 2011

2011 IEEE PES Trondheim PowerTech: The Power of Technology for a Sustainable Society, POWERTECH 2011

Trondheim, 19 June 2011 through 23 June 2011

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-008-0GR

DOI: 10.1109/ptc.2011.6019390

Abstract (EN): This paper analyzes the application of the Information Theoretic (IT) Mean Shift algorithm for modes finding in order to provide the classification of Electricity Customer Load Patterns. The impact of the algorithm parameters is discussed and then clustering indices are used in order to make a comparison with the classical methods available. Results show a good capability of the modes found in capturing the data structure, aggregating similar load patterns and identifying the uncommon patterns (outliers). © 2011 IEEE.

Language: English

Type (Professor's evaluation): Scientific