University of Oulu

Hietaharju, P.; Ruusunen, M.; Leiviskä, K. A Dynamic Model for Indoor Temperature Prediction in Buildings. Energies 2018, 11, 1477.

A dynamic model for indoor temperature prediction in buildings

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Author: Hietaharju, Petri1; Ruusunen, Mika1; Leiviskä, Kauko1
Organizations: 1Control Engineering, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018061425862
Language: English
Published: Multidisciplinary Digital Publishing Institute, 2018
Publish Date: 2018-06-14
Description:

Abstract

A novel dynamic model for the temperature inside buildings is presented, aiming to improve energy efficiency by providing predictive information on the heat demand. To analyse the performance and generalizability of the modelling approach, real measurement data was gathered from five different types of buildings. Easily available data from various sources was utilized. The chosen model structure leads to a minimal number of input variables and free parameters. Simulations with real data from five buildings, and applying the identical model structure showed that the average modelling error during the 28-h prediction horizon was constantly below 5%. The results thus demonstrate that the model structure can be standardized and easily applied to predict the indoor temperatures of large buildings. This would finally enable demand side management and the predictive optimization of the heat demand at city level.

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Series: Energies
ISSN: 1996-1073
ISSN-E: 1996-1073
ISSN-L: 1996-1073
Volume: 11
Issue: 6
Article number: 1477
DOI: 10.3390/en11061477
OADOI: https://oadoi.org/10.3390/en11061477
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This research was funded by the Finnish Funding Agency for Innovation (TEKES) through the project KLEI (40267/13) and the Academy of Finland through the project SEN2050 (287748).
Academy of Finland Grant Number: 287748
Detailed Information: 287748 (Academy of Finland Funding decision)
Copyright information: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
  https://creativecommons.org/licenses/by/4.0/