Energy performance regression models for office buildings with daylighting controls

Abstract

Sensitivity analysis is performed to observe the response of the system when a given design parameter is changed. It is important to know the relationships between the input parameters and output results such that appropriate design variables can be selected to achieve the optimum building energy performance. This paper studies the sensitivity of energy performance and establishes regression models for office buildings with daylighting designs in Hong Kong. The building energy simulation computer program, namely EnergyPlus, was used to generate data for the analysis. The important input design parameters affecting the daylighting schemes were identified and analysed in terms of annual building electricity expenditures and peak electrical demands. Four building envelope design parameters, namely, window-to-wall ratio, light transmittance of windows, projection ratio of overhang, and projection ratio of side-fins were found to correlate well with the predicted incremental electricity use (IEU) and incremental peak electricity use (IPEU). Both linear and non-linear multiple regression techniques were used to develop regression models and energy equations for the predictions of IEU and IPEU. Statistical results show that such models and equations can be used to evaluate the energy performance of various building envelope design schemes for building with daylighting controls during the early design stage.