Publications / 2014 Proceedings of the 31st ISARC, Sydney, Australia

Predicting Energy Usage Using Historical Data and Linear Models

Majeed Safa, Jeremy Allen, Mahdi Safa
Pages 531-535 (2014 Proceedings of the 31st ISARC, Sydney, Australia, ISBN 978-0-646-59711-9, ISSN 2413-5844)

This paper presents a method to predict energy usage, based on weather conditions and occupancy, using a multiple linear regression model (MLR) in research office buildings. In this study, linear regression models of four research office sites in different regions of New Zealand were selected to show the capability of simple models to reduce margins of error in energy auditing projects. The final linear regression models developed were based on monthly outside temperatures and numbers of full time employees (FTEs). Comparing actual and predicted energy usage showed that the models can predict energy usage within acceptable errors. The results also showed that each building should be investigated as an individual unit.

Keywords: Energy prediction, energy auditing, linear regression model, office buildings, energy saving, optimization