Customized building operations: Defining operational signatures of HVAC system configurations through data analytics on historical BAS data

 This study aims to identify critical parameters of HVAC systems that drive the changes in the building energy-use profiles and develop an automated approach for identifying HVAC operational signatures that result in certain energy profiles in buildings, OperAtional Signature Identification System (OASIS). The OASIS relies on data-driven methodologies and is composed of three major steps: data preprocessing, feature selection, and signature discovery and analysis. The approach was tested on several air handling units (AHUs). The results showed that it is possible to define operational signatures for facility operators that are specific to a given building for running AHUs at these custom settings that correspond to energy efficient consumption in buildings.


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