EMIS ReportDesign-Prelim 2020sep11 - Page 12

term data snapshot of building performance; The
and Lin 2016). Study participants reported that this
advent of EMIS has enabled these commissioning
performance would not have been possible without the
providers to provide automated analytics in real time.
EIS. A wide range of costs were also found, with total
MBCx may be used during an EBCx process
costs of EIS software ranging over two to three orders
to streamline and automate data analysis during
of magnitude.
the investigation process and after EBCx to track
Research results on the costs and benefits of
whether energy savings persist and find additional
commercialized FDD products are less available than
opportunities over time.
those for EIS. A study on FDD for commercial buildings
While MBCx is a recommended best practice, many
provided a thorough characterization of functionality
organizations have successfully implemented EMIS
and application for 14 FDD technologies (Granderson
without a defined MBCx process. In the absence of
et al. 2017); however, the study scope did not include
formal MBCx, the EMIS may be integrated into daily
quantification of costs or benefits. Based on an
building operations as a support tool,
analysis of the most common faults
Analytics can help owners
helping to drive facility management
in building systems, studies estimate
processes and enable data-driven
that the energy savings achievable
the proactive by detecting
decision making.
from addressing these faults range
equipment cycling issues
from 5 to 30 percent whole building
EMIS Technology Benefits
savings (Fernandez et. al 2017; Roth
and avoiding unnecessary
Energy and cost savings are often
et. al 2005).
wear and tear that can
a driving factor in the decision to
To allow for comparison of the
reduce equipment life.
implement an EMIS. The number
savings analysis with past research,
of commercially available EMIS has increased
all studies available that document savings or payback
dramatically over the past decade, driven by the
are shown in Table 1. While there are a few instances
increased availability of higher-granularity energy
of payback calculated for EIS, there has not been FDD
(generally 15-minute to hourly) and BAS time series
software costs published the research. The lack of
data. Building staff can leverage these data to
savings and cost data available for EMIS points to the
continuously monitor building performance and
need for more cost-benefit research and thus the focus
automate analysis through EMIS, leading to energy
of this research project.
savings, peak demand reduction, and a reduction
Challenges in EMIS Use
in service calls. Further, analytics can help owners
move from the reactive to the proactive by detecting
With numerous vendors and feature packages
equipment cycling issues and avoiding unnecessary
available, it becomes difficult for owners to determine
wear and tear that can reduce equipment life. To
which type of EMIS will support their needs and meet
support owners in these aims, Lawrence Berkeley
thresholds for return on investment. Even if there
National Laboratory (LBNL) created a resource that
is adequate energy metering in place, it is common
summarizes how both EIS and FDD can be used to
to have problems integrating the data into the EMIS
identify energy saving opportunities in commercial
due to legacy data sources, varying communications
buildings (Lin et al. 2017). In addition to operational
protocols, and cybersecurity needs. It can be difficult
improvements, EMIS can be used to verify energy
to get disparate data collection systems into a single
savings for many measures.
database to integrate with the EMIS.
EMIS are most often implemented as a part of an
In addition to metering and data management
overall energy management approach that includes
hurdles, a common challenge is the lack of staff time
retrofits and commissioning. Thus, the benefits of
to review the EMIS dashboards and reports, and to
using EMIS are difficult to isolate from other actions. In
investigate and implement recommended findings.
one EIS-focused study of 28 buildings and 9 portfolios
Staff may experience data overload if their EMIS
across the United States, energy savings ranged
is not configured properly, or if there is not enough
from -3 to 47 percent with a median of 17 percent
automation of the analytics. With EIS, there may be
for individual buildings, and from 0 to 33 percent
difficulty in pinpointing opportunities in the data,
with a median of 8 percent for portfolios (Granderson
and with FDD there are often challenges definitively
Berkeley Lab | Proving the Business Case for Building Analytics

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