An Iterative Methodology for Model Complexity Reduction in Residential Building Simulation

The present paper introduces an iterative methodology to progressively reduce building simulation model complexity with the aim of identifying potential trade-offs between computational requirements (i.e., model complexity) and energy estimation accuracy. Different levels of model complexity are ana...

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Bibliographic Details
Published in:Energies (Basel) 2019-06, Vol.12 (12), p.2448
Main Authors: De Rosa, Mattia, Brennenstuhl, Marcus, Andrade Cabrera, Carlos, Eicker, Ursula, Finn, Donal P.
Format: Article
Language:English
Subjects:
Accuracy
Alternative energy
Building envelopes
building simulation
Calibration
Computer simulation
Cooling
Demand side management
Economic forecasting
Electricity distribution
Energy consumption
Energy demand
Energy efficiency
Energy management systems
energy performance forecasting
External walls
Flexibility
Green buildings
Heat exchangers
Heat pumps
Legislation
Low temperature
model calibration
Nodes
reduced models
Residential buildings
smart grids
Thermal analysis
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Summary:The present paper introduces an iterative methodology to progressively reduce building simulation model complexity with the aim of identifying potential trade-offs between computational requirements (i.e., model complexity) and energy estimation accuracy. Different levels of model complexity are analysed, from commercial building energy simulation tools to low order calibrated thermal networks models. Experimental data from a residential building in Germany were collected and used to validate two detailed white-box models and a simplified white-box model. The validation process was performed in terms of internal temperature profiles and building thermal energy demand predictions. Synthetic profiles were generated from the validated models and used for calibrating high order models. A reduction (trimming) procedure was applied to reduce the model complexity using an energy performance criterion prior to model trimming. The proposed methodology has the advantage of keeping the physical structure of the original RC model, thus enabling the use of the trimmed lumped parameter building model for other applications. The analysis showed that it is possible to reduce the model complexity by half, while keeping the accuracy above 90% for the targeted building.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12122448