Assessing the implications of submetering with energy analytics to building energy savings

Abstract

Abstract This paper analyzes the effect of the depth of submetering (i.e., from whole-building level to system level to equipment level and further to sensor level) on the energy savings that can be achieved in energy analytics or energy information system (EIS) implementations. An EIS is defined as a combination of software and hardware systems that gather energy-related data, feed it into an analytics engine, and present building operators with analyses that allow them to reduce energy consumption. Data regarding the energy savings, the depth of submetering in the EIS implementation, and the cost of submetering was gathered for 21 case (building portfolio) studies and analyzed to determine if there is a relationship between the depth of submetering and the energy savings achieved. It was found that in general, deeper submetering does in fact appear to enable deeper energy savings. The one exception to this is sensor-level data: the addition of detailed sensor level metering to other higher levels of metering data does not seem to enable deeper energy savings in EIS implementations. Detailed findings in energy savings, cost and cost-effectiveness were presented for different levels of metering that may provide insightful rule-of-thumb estimations for similar implementations.