We Don't Know What We Don't Know: Data Mining Retail Banking Center Performance Benchmarking Assets for Sustained Behavioral Transformation

摘要

As the energy efficiency in new buildings continues to improve through the application integrated design strategies; plug loads and certain critical operational loads that are intrinsic to practice remain the primary invisible consumers of a vast part of the built environments overall energy profile (1). This paper will present the results of a yearlong study intended to measure how detailed benchmarking can be used within the context of a specific, existing building use type. This study of branch banking centers addresses load profiles across two different periods of construction (i.e., ASHRAE 90.1-1989 & Current LEED Standard). These two buildings are representative of the cross section of those currently in operation, and form the backbone of the managed assets, each preforming similar services. The study addressed the significant amount of data available from these assets, asking these questions beyond the aggregate of HVAC, lighting and plug loads: 1. Can data be mined to identify trends for prototypical operations such as typical work station behavior/ office profiles (i.e., PCs, monitors, printers and auxiliary equipment, interior and exterior lighting); as well as those loads that are determined to be uninterruptable (i.e., computer servers; ATMs; ATM and emergency lighting)? 2. Can the benchmarking results be used to establish a cohesive retrofit guideline looking toward significant emphasis on operational cost reduction? 3. With significant data available from a comparative sample of sites and similar use patterns, can data be mined to define a protocol, around meaningful trends, that help to establish retrofit guidelines across all corporate assets?