EMIS ReportDesign-Prelim 2020sep11 - Flipbook - Page 5
Monthly Data Analytics
Energy Information System
• Interval Meter Data Analytics
• Advanced M&V
(Measurement and Verification)
FIGURE ES-1: Data inputs and key capabilities of EMIS
Fault Detection and Diagnostics
Automated System Optimization
The Smart Energy Analytics Campaign was conceived
as an opportunity to assess the costs, benefits, and
common practices of EMIS when deployed at scale
across a wide array of building types and sizes.
Subhead Goes Here
The Campaign coupled technical assistance
with qualitative and quantitative data collection.
Participants are encouraged to share their progress
and may receive national recognition. After three years
in operation, the Campaign included 104 commercial
organizations across the United States, totaling 567
million square feet of gross floor area and more than
6,500 buildings, making this the most comprehensive
dataset available on analytics installation and use. The
dataset includes nine different market sectors (with
office and higher education accounting for 80 percent
of participants), and with a wide range of portfolio
sizes. This report presents a characterization of EMIS
costs and benefits, MBCx services, and trends in the
industry based on data from these organizations.
By the second year of installation, study participants
with energy information systems1 (EIS) achieved a
median annual energy savings of 3 percent ($0.03/sq
ft) and participants with fault detection and diagnostic
tools2 (FDD) achieved a median savings of 9 percent
($0.24/sq ft).3 Applied across the organizations
participating in the Smart Energy Analytics Campaign,
Energy information systems (EIS) are the software, data acquisition hardware, and communication systems used to store, analyze, and
display building energy data.
Fault detection and diagnostic (FDD) tools are the software that automates the process of detecting faults and suboptimal performance of
building systems and helps to diagnose their potential causes.
Energy savings reported from sites with at least two years of EMIS implementation. The median savings are determined by comparing
energy data from the second year after EMIS implementation with the baseline year before the EMIS was installed.
Berkeley Lab | Proving the Business Case for Building Analytics