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Clustering baseline data: end users and energy consumption

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Last steps of the ENCERTICUS Baseline:  integrating sociocultural data and end users' attitudes to the consumption data.

The ENCERTICUS MED Project has collected data on energy and water consumption of three pilot sites, as well as those provided by participants in personal interviews during the first months of 2014. The sociological methods applied give information like behaviour, habits and attitudes of users towards energy consumption which are often left aside in similar projects and used only as a mere process of the project as they are difficult to integrate into the project context.


Cluster analysis or clustering is the collection of methods for clustering unlabelled data into subsets (called clusters) that reflect the underlying structure of the data, based on similarity groups within the data.
In other words, a set of objects in the same group are more similar to each other than to those of other groups. The number of clusters have been chosen based on initial tests and values of the silhouette index defining the optimal number of clusters. The silhouette index contrasts the average distance of elements in the same cluster with the average distance of elements in other clusters. After cluster analysis, a cluster profile has being drawn, using it as a baseline for evaluating savings following service implementation.