Load forecast on intelligent buildings based on temporary occupancy monitoring

Jose A. Oliveira-Lima, Ramiro Morais, J. F. Martins, Adrian Florea, Celson Pantoja Lima

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

The modeling of energy consumption in buildings must consider occupancy as a relevant input, since it plays a very important role in the overall building's energy consumption. Frequently, buildings lack of permanent occupancy monitoring solutions. However, they may include data sources that are correlated with real building occupancy. This study proposes a new methodology for energy consumption modeling, supported by these alternative data sources, such as the number of vehicles in a parking lot. The aim is to mitigate investment in permanent occupancy monitoring solutions. The proposed methodology makes use of short-term real occupancy monitoring for model fitting, to enable the development of occupancy and energy consumption models, based on these alternative data sources.

Original languageEnglish
Pages (from-to)512-521
Number of pages10
JournalEnergy and Buildings
Volume116
DOIs
Publication statusPublished - 15 Mar 2016

Keywords

  • Building occupancy
  • Energy consumption forecasting
  • Intelligent buildings
  • Neural networks
  • Parking lot occupancy

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