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A dynamic model for indoor temperature prediction in buildings
- Source :
- Energies, Vol 11, Iss 6, p 1477 (2018), Energies, Volume 11, Issue 6
- Publication Year :
- 2018
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2018.
-
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.
- Subjects :
- Mathematical optimization
grey-box model
Control and Optimization
Horizon (archaeology)
Renewable Energy, Sustainability and the Environment
Computer science
lcsh:T
020209 energy
indoor temperature prediction
Energy Engineering and Power Technology
02 engineering and technology
7. Clean energy
lcsh:Technology
cross-validation
thermal modeling
11. Sustainability
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
parameter estimation
Engineering (miscellaneous)
Energy (miscellaneous)
Efficient energy use
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Energies, Vol 11, Iss 6, p 1477 (2018), Energies, Volume 11, Issue 6
- Accession number :
- edsair.doi.dedup.....df4281f296bffb088e21f5e77acbdd1a