Development, Implementation, and Industry Reception of a Novel Multi-source, Data-driven Building Energy Management Toolkit

Abstract

Building energy performance is often negatively impacted by inefficient and uninformed operations, leading to wide disparities between predicted and actual energy use in commercial and institutional buildings. Though ample research in data-driven building operations and maintenance analytics has derived various methodologies for extracting energy-saving insights that can supplement operating practice, these approaches have traditionally remained disparate, limiting their application, and are exclusively prevalent in academia. Furthermore, operations personnel who regularly manage controls and maintenance of HVAC equipment can benefit from these novel approaches in augmenting their duties and optimizing building energy efficiency. This research explores the development of a novel multi-source, data-driven building energy management toolkit as a synthesis of established data-driven approaches in the literature comprising inverse energy modelling, anomaly detection and diagnostics, load disaggregation, and occupancy and occupant complaint analytics methods. The toolkit inputs various data types to detect hard and soft faults, optimize sequences of operation settings, and monitor energy flows, occupancy patterns, and occupant satisfaction. The toolkit's unique multi-source analytical approach was used to pinpoint operational deficiencies stemming from inappropriate zone temperature overheating thresholds and perimeter heating devices. Energy-saving insights were generated using data from four separate case study buildings to demonstrate the utility of the toolkit's web-based application platform. Finally, interviews with building operators and facility managers to their interpretations of insights from data-driven approaches were conducted; possible barriers were identified which inhibited industry professionals from effectively deriving and utilizing insights from the visualizations and KPIs.