Getting Valuable Information Out of your Building`s Big Data

March 20-April 2, 2013 — COLORADO REAL ESTATE JOURNAL — Page 15B
Group 14 Engineering
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Getting Valuable Information
Out of your Building’s Big Data
odern buildings
produce massive
amounts of data,
from zone temperature readings
to major mechanical equipment
sensors to energy meters. A single
building can generate hundreds
of thousands of data points per
day. Now, all of that data can be
turned into valuable information.
Recent software advancements
allow strong analytic capabilities
to be cost-effectively integrated
into existing building automation
system platforms. These
enhanced platforms use energy
use and equipment performance
data to deliver meaningful,
actionable information to the
team members who need it. At
the portfolio or facility level, this
information can be used to make
high return investments, reduce
risk, allocate personnel in a more
efficient manner, and increase
your competitive edge against
comparable buildings.
There are often many
efficiency opportunities with
less than a year payback at any
given facility. Rather than rely
on a static, one-time audit or
retro-commissioning process,
building analytics generates key
performance indicators (KPIs)
on an ongoing basis. This allows
for quick, real-time opportunity
Brody Wilson
Brian Graham
Energy Engineer,
Group 14 Engineering, Denver
Energy Engineer,
Group 14 Engineering, Denver
identification across an entire
portfolio.
A process known as automated
fault detection and diagnostics
(FDD) can be coupled to
the data analytics software to
automatically indicate when
and where issues have occurred
in the building. From large
energy opportunities, like poorly
performing chilled water plants,
to smaller ones, like VAV boxes
unable to maintain setpoint, the
software can apply rules against
the incoming data to determine
modes of operation that are not
working correctly. These faults
are then prioritized in order
to make best use of limited
maintenance budgets and staff
time. Resolving these issues in a
targeted fashion saves energy and
improves comfort.
Thermal comfort can now be
proactively managed. Building
analytics transform building
automation system zone
temperature alarms into pushed
alerts, with probable cause and
remedy already identified. Alerts
can change based on the amount
of deviation from desired
temperature setpoint, helping
facility staff to separate out and
address critical problems before
they turn into tenant complaints.
Building analytics can also help
managers accurately determine
common area maintenance
(CAM) and energy costs. A
typical approach is to allocate
the building’s total CAM and
energy costs to each tenant on a
per square foot basis. While this
is attractive to an existing, energyintensive tech company tenant, it
can turn off prospective tenants
who would have to foot the bill
for the existing tenants’ high
energy use. Building analytics
can be used to make this process
fair, transparent and accurate. By
combining meter and sub-meter
readings with available sensor
data, “virtual” meters can be set
up to justify costs to each tenant
based on actual use, rather than
leased square footage. Accurate
allocation of costs can lead to
more competitive lease rates
and a more profitable rent roll,
both key elements of a successful
building.
Initial deployment of data
analytics software does require
the skills of both a software
engineer and a mechanical
engineer. The software engineer
is needed to integrate the
building automation system data
into the data analytics program.
After the data is piped into
the software, the mechanical
engineer can analyze the
building systems to write rules
for fault detection, setup the
necessary KPI visualization and
conduct system tuning to ensure
the reported data is accurate and
reliable. Once the rules have
been tuned to ensure accurate
operator feedback, the software
is essentially standalone. This “set
it and forget it” capability allows
portfolio managers, building
managers, and facility teams to
use the available data to drive
their business decisions with
greater confidence and more
reliable results.
The bottom line is that
deploying data analytics software
at your facility or across your
building portfolio can lead to
more competitive lease rates,
higher tenant satisfaction, and
lower operating costs. When used
correctly, Big Data is a powerful
driver of building profitability.
ENGINEERING