Abstract
Health Services building stock is usually the top energy consumer in the Administrative sector, by a considerable margin. Therefore, energy consumption supervision, prediction, and improvement should be carried out for this group in a preferential manner. Most prior studies in this field have characterized the energy consumption of buildings based on complex simulations, which tend to be limited by modelisation restrictions and assumptions. In this paper, an improved method for the clusterization of buildings based on their electrical energy consumption is proposed and, then, reference profiles are determined by examining the variation of energy consumption over the typical yearly consumption period. The temporary variation has been analyzed by evaluating the temporary evolution of the area consumption index through data mining and statistical clusterization techniques. The proposed methodology has been applied to building stock of the Health Services in the Castilla y León region in Spain, based on three years of historical monthly electrical energy consumption data for over 250 buildings. This building stock consists of hospitals, health centers (with and without emergency services) and a miscellaneous set of administrative and residential buildings. Results reveal five distinct electrical consumption profiles that have been associated with five reference buildings, permitting significant improvement in the demand estimation as compared to merely using the classical energy consumption indicators.
Highlights
In order to comply with European Union (EU) perspectives on energy generation and consumption by EU members for the 2030 and 2050 horizons, a significant increase in the penetration of renewable energy sources (RES) and a reduction of energy needs, through energy savings and efficiency policies, are mandatory
Reliable energy indexes must be developed in order to supervise the evolution of the consumed energy, which is associated with greenhouse effect gas emissions
The aim of this work is to identify general classes of buildings according to their electric energy consumption and to improve the demand estimations, and the aggregation of electric energy profiles of different buildings, which results truly useful for centralized energy purchasing, energy consumption monitoring by activity sectors and fast identification of abnormal consumption behaviors
Summary
In order to comply with European Union (EU) perspectives on energy generation and consumption by EU members for the 2030 and 2050 horizons, a significant increase in the penetration of renewable energy sources (RES) and a reduction of energy needs, through energy savings and efficiency policies, are mandatory. Both approaches are especially relevant in the transport and buildings sectors, and within the latter, Public Administration building stock is of special relevance. This method has been demonstrated to show a great accuracy in some specific
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