Electrical Consumption Profile Clusterization: Spanish Castilla y León Regional Health Services Building Stock as a Case Study
Open Access
- 6 December 2018
- journal article
- research article
- Published by MDPI AG in Environments
- Vol. 5 (12) , 133
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.Keywords
This publication has 29 references indexed in Scilit:
- Data mining based framework for exploring household electricity consumption patterns: A case study in China contextJournal of Cleaner Production, 2018
- Identification of representative buildings and building groups in urban datasets using a novel pre-processing, classification, clustering and predictive modelling approachBuilding and Environment, 2018
- Pattern recognition in building energy performance over time using energy benchmarking dataApplied Energy, 2018
- Determining key variables influencing energy consumption in office buildings through cluster analysis of pre- and post-retrofit building dataEnergy and Buildings, 2018
- Building energy retrofit index for policy making and decision support at regional and national scalesApplied Energy, 2017
- Worldwide Research on Energy Efficiency and Sustainability in Public BuildingsSustainability, 2017
- k-Shape clustering algorithm for building energy usage patterns analysis and forecasting model accuracy improvementEnergy and Buildings, 2017
- Developing a Rating System for Building Energy Efficiency Based on In Situ Measurement in ChinaSustainability, 2017
- A statistical modeling approach to detect anomalies in energetic efficiency of buildingsEnergy and Buildings, 2016
- Energy consumption and efficiency in buildings: current status and future trendsJournal of Cleaner Production, 2015