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

Inefficient and uninformed operations negatively impact building energy performance, leading to wide disparities between predicted and actual energy use in commercial and institutional buildings. Though ample research in data-driven building operations analytics has derived various methodologies for extracting energy-saving insights that can inform best practices, these approaches have traditionally remained disparate, and are mostly inaccessible to operations personnel who can benefit from these approaches in augmenting their duties and optimizing building energy efficiency. This research explores the development, implementation, and industry reception of a novel multi-source, data-driven building energy management toolkit as a synthesis of established data-driven approaches in the literature. Energy-saving insights identified from over five separate case study buildings demonstrated the toolkit's multifaceted application to identify operational deficiencies, and interviews with building operators and facility managers regarding the toolkit's outputs were conducted to identify possible barriers which may inhibit operations professionals from effectively deriving and utilizing data-driven insights.