Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Energy Consumption Modeling by Machine Learning from Daily Activity Metering in a Hospital
Year:2017
Research Areas
  • Civil engineering,
  • Constructions
Information
Abstract
Hospitals are large buildings that consume a great amount of energy mostly due to their continuous energy consumption needs, high consumer medical equipment, and special requirements of thermal and air conditions. Reliable dynamic simulation is a chimera because of the complex design and behavior of these buildings. Therefore, monitoring-based methods arise as a plausible alternative. Its main drawback, however, is the lack of enough data to generate statistically robust models. The paper faces this problem thanks to the helpful contribution of a collaborative hospital which was able to generate daily data of electrical energy consumption for a period of six years. Besides, thirteen variables that summarize the daily activity of the hospital are also included. The results show how machine learning techniques generate models that accurately predict the electrical energy consumption based on weather conditions and activity measurements. The obtained results are useful for the design of more specific energy saving strategies, a more efficient economic investment for energy retrofitting of existing buildings and a better management of economic energy cost in large-scale buildings.
International
Si
Congress
22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2017)
960
Place
Limassol, Cyprus
Reviewers
Si
ISBN/ISSN
978-1-5090-6505-9
10.1109/ETFA.2017.8247667
Start Date
12/09/2017
End Date
15/09/2017
From page
1
To page
7
Conference Paper ETFA2017
Participants
  • Autor: Elena Ruiz (Universidad de Granada)
  • Autor: Rosalia Pacheco Torres (UPM)
  • Autor: Jorge Casillas (Universidad de Granada)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Tecnología de Materiales y Medio Ambiente
  • Departamento: Ingeniería Civil: Construcción, Infraestructura y Transporte
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)