Paper Conference

Proceedings of Building Simulation 2011: 12th Conference of IBPSA

     

Calibrating Micro-Level Models With Macro-Level Data Using Bayesian Regression Analysis

Adam Thomas Booth, Ruchi Choudhary

DOI: https://doi.org/10.26868/25222708.2011.1296
Abstract: Bottom-up engineering-based housing stock models play a useful role in assessing the impact of retrofits for residential buildings. Such models require calibrating, using micro-level energy measurements, to improve model accuracy; however, the only publicly available data for the UK housing stock is at the macro-level. This paper outlines a method for using macro-level data to calibrate micro-level models. A combination of regression analysis and Bayesian inference is proposed. The result is a Bayesian regression method that generates estimates of the average energy use for different dwelling types, whilst quantifying uncertainty in the empirical energy data and the generated energy estimates.
Pages: 641 - 648
Paper:
bs2011_1296