Estimation of Building Parameters Using Simplified Energy Balance Model and Metered Whole Building Energy Use

Abstract

This paper presents and evaluates an indirect data-driven method to estimate influential building parameters: air exchange rates and overall heat transfer coefficients of building envelopes from the separately metered energy use for electricity, cooling and heating and weather data using multiple linear regression models based on the simplified steady-state energy balance for a whole building. Two approaches using different response variables: the energy balance load (EBL) and the building thermal load (QB) and the use of monthly and daily interval data are evaluated using the synthetic data and the measured data from three large dormitory buildings. Although this method is not expected to replace actual measurement, easy and fast access to the influential building parameters allows new applications such as in preliminary investigation for energy conservation projects.