Office representatives for cost-optimal energy retrofitting analysis: A novel approach using cluster analysis of energy performance certificate databases

Abstract

A large number of buildings must be evaluated to formulate energy retrofitting policies for existing building stock. In this context, it is crucial to identify reference buildings that can effectively represent the entire stock, since such buildings can then be used to assess the individualized cost-effectiveness of retrofitting measures. This paper presents a novel approach for identifying and defining a set of reference buildings by applying the k-means clustering method to energy performance certificate databases. To this end, a four-step methodology has been envisaged. First, an energy performance certificate database is prepared and variables that have an impact on energy consumption are pre-selected. Selected data are then pre-processed. Next, the k-means clustering method is applied. Finally, the resulting cluster centroids are used to identify the closest energy performance certificates in the database, in other words, the representative buildings that will then be used for cost-optimal retrofitting analysis. The methodology is illustrated using the energy performance certificate database managed by the Catalan Institute of Energy (ICAEN), which includes a sample of 13,701 offices. Due to the large number of missing values in the database, the k-means clustering algorithm was finally performed over 6,083 energy performance certificates. Seven representative office blocks and offices in industrial buildings and nine representative offices in residential buildings were identified. The results establish the basis for supporting strategic decision-making for energy saving retrofit interventions in existing Spanish offices. © 2019