Role of big data analytics in building energy savings
Abstract: With the development of automatic meter reading systems, massive high-resolution energy usage data from buildings can now be easily collected with a reasonably low cost. This massive amount of data provides a great opportunity to assist in better understanding building energy usage characteristics and operational performance, and in extracting the useful and hidden information to support the areas including but not limited to building energy performance assessment and benchmarking, building load estimation and demand side management, occupant behavior prediction, and fault detection and diagnosis of heating, ventilation and air-conditioning systems. This presentation will introduce a range of data analytic strategies to improve building energy efficiency. The main findings can be used to facilitate energy planning and develop high performance buildings and precincts.
Speaker: Dr Zhenjun Ma is an Associate Professor at the Sustainable Buildings Research Centre, University of Wollongong, Australia. He has been working extensively on building energy efficiency, building big data analytics and low carbon heating and cooling technologies. He has been a recipient of several prestigious awards and academic recognition such as an Australian Endeavour Research Fellowship Award and the UOW Impact Maker. His research findings have been widely referenced by researchers across the world.
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