Article Title
Predictive capability testing and sensitivity analysis of a model for building energy efficiency
Keywords
building energy modelling, energy consumption assessment, model sensitivity analysis, model predictive capability
Abstract
Building energy modelling presents a good tool for estimating building energy consumption. Different modelling approaches exist in literature comprising white-box/physical/calculation-based models, black-box/statistical/measurement-based models or hybrid models combining the former two. Our work presented in this paper deals with a calculation-based quasi-steady-state model for building energy consumption based on the ISO 13790 standard and its implementation in MATLAB/Octave. The model is also well compared to the ISO 52016 standard updating ISO 13790. The model predictive capability is confirmed against both EnergyPlus dynamic simulator results and calculation results of a commercially available relevant tool used as benchmarks. Machine learning techniques are applied to a large dataset of simulated data and a sensitivity analysis is presented narrowing down to the most influential model parameters.
Publisher
Tsinghua University Press
Recommended Citation
G. Kalogeras, S. Rastegarpour, C. Koulamas et al. Predictive capability testing and sensitivity analysis of a model for building energy efficiency. Build Simul, 2020, 13(1): 33–50.
