Dynamic data processing for building energy consumption

Abstract

With the growing attention to smart buildings, local governments are seeking practical ways to optimize the energy consumption of commercial buildings. An ideal smart building is capable of monitoring its own energy consumption and adjusting the operation of electric devices, being lighting and air conditioners, based on the occupant behaviour. In this study, data had been obtained from the monitoring sensors in a commercial building located in the heart of Sydney from 2013 until 2020 on a 15-minute time intervals. The data derivation and analysis are intrinsically static at the moment which makes it difficult for building management to make instantaneous decision regarding the measures to be taken for a lower energy consumption. Using data analysis and visualization tools in Tableau, this study provides detailed insights about the trends in energy consumption in the given building. The outcomes facilitate the decision making for building management and can be seen as a milestone towards a dynamic optimization protocol in a bigger picture which is introduced in the second part of this study.