Comparing time-series clustering approaches for individual electrical load patterns
24th International Conference & Exhibition on Electricity Distribution (CIRED)
SESSION 5: PLANNING OF POWER DISTRIBUTION SYSTEMS
CIRED | Open Access Proceedings Journal June 2017
Authors: Zacharie De Greve ; Fabian Lecron ; François Vallee ; Gerard Mor ; Daniel Pérez ; Stoyan Danov ; Jordi Cipriano
This work positions the task of grouping electricity load time series among the vast field of clustering, and highlights corresponding research issues. A selection of the most performant time-series clustering approaches from the signal processing community are compared on the same dataset, composed by domestic electricity load profiles from Spain. The cross-correlation-based distance of Paparrizos and Gravano (2015) is shown to provide the best tradeoff between clustering accuracy and CPU times.