Energy modelling software such as EnergyPlus can be used for developing analysis tools to monitor and analyse the energy efficiency of buildings. However, such software usually require high proficient experts taking considerable amount of time to develop the energy model which is highly customised for buildings with different equipments. In addition, it is often challenging to integrate the energy model with existing building energy management systems (BEMS).
The technology described herein is related to the development of a machine learning model which can optimise building operations based on building data from the building management system and hence, achieve building energy efficiency. The model, which can be installed in BEMS servers, possesses the capability to diagnose areas of inefficiency and provide inputs to control building equipment operations (e.g. pumps, cooling towers and chillers).
The machine learning model for optimising building performance consists of the following specifications:
The technology is applicable for the building energy management industry where it can be integrated with building management system to diagnose areas of energy inefficiency and provide insights to forecast energy consumption in buildings.
The market size of BEMS is expected to grow almost quadrupled in size, and will be worth over $1 billion by 2020, according to a report by Pike Research.