26 ELECTRICALCONTRACTOR | OCT. 14 | WWW.ECMAG.COM
UTILITY-SCALE RENEWABLES 3.0
manufacturers, such as Alstom, GE,
Siemens and Vestas, market equipment capable of producing up to 7. 5
MW each (though most U.S wind
farm turbines max out closer to 3
MW). Reaching this performance
level, however, requires manufacturers to think big—really big. The
blades of a Siemens 3-MW turbine are
180 feet long. Add that to a tower that
could reach 400 feet tall, and the result is a
structure that stretches 580 feet from blade
tip to the ground.
In addition to climbing ever higher,
turbine experts are investigating what
they can do to push more energy out of this equipment by
helping it operate more intelligently. GE leads this field, having recently announced two new offerings intended to boost
productivity and profitability at existing wind installations by
looking at individual turbines and entire farms.
The company’s PowerUp Analytics package enables technicians to assess and fine-tune specific categories of turbine
operation, such as blade pitch, torque, speed and the orientation of the nacelle—the housing for turbine mechanics at the
point where the blades come together—for an incremental
increase in performance that can have an outsize effect on a
wind farm’s bottom line.
“Turbines are designed for certain wind conditions. How-
ever, where they are actually sited is different than what the
designed conditions might be,” said Keith Longtin, general
manager wind products in GE’s renewable-energy division.
“We are always thinking about how we can get even more
power out of the asset.”
The company estimates the PowerUp program can boost a
wind farm’s overall performance by up to 5 percent, which can
lead to a 20 percent boost to the owner’s bottom line.
“The figure is the result of the turbine being more profitable
without increasing costs or depreciation,” Longtin said. “[This]
provides our customers with enhanced economics and higher
efficiency from their farms.”
Utility crystal ball
Despite improvements that can help solar and wind facilities
act more like base-load generation, their intermittent nature
can still wreak havoc at all levels of the electricity grid, from
regional transmission systems down to neighborhood-level distribution transformers. Big data is beginning to help utilities and
transmission-system operators predict such system anomalies
before they happen and present that information in a way that
has meaning to the person sitting in front of a computer terminal.
“We take data from different sources; we analyze and visual-
ize it,” said Steve Ehrlich, senior vice president of San Mateo,
Calif.-based Space-Time Insight. The
company, which launched in 2008,
has seven of the top 20 U.S. utili-
ties as customers, and it is helping
improve insight into grid operations,
from the level of the independent
system operator (California’s inde-
pendent system operator is a client)
down to individual customer meters.
For large-scale solar and wind
integration, Space-Time Insight can tie near-
real-time weather forecasting to specific
wind and solar farms to provide updated
forecasts of how much actual electricity
those facilities can be expected to produce.
“It’s what we call translating big data into little data,”
The Sacramento Municipal Utility District (SMUD) is
another customer, and its planners are taking Space-Time
Insight’s translation skills down to the customer level to help
understand the effect of rooftop PV panels, and they have
learned how electric vehicles (EVs) can affect the local distribution grid.
“It turned out that, the first time anyone plugged in their
Tesla, they used many more cycles than expected,” Ehrlich said.
So, SMUD began tracking EV households, even accessing Department of Motor Vehicle information on owner
addresses and vehicle type (because every EV has different charging characteristics) to better understand potential
“They need to balance the grid. If they don’t have enough
capacity in a neighborhood, they need to add to that,” he said.
With a vast range of specific data on assets—such as transmission and distribution substation locations, high-voltage line
availability and other information—the software also can help
planners understand where new capacity, including solar and
wind installations, makes the most sense and where it doesn’t.
Users can simply mouse around a data-populated map, and
sweet-spot locations will show up as green on their screen.
All of this is leading to the capability to, essentially, predict
the future. With enough information about equipment condition, system demands, upcoming weather events and other
critical factors, grid operators working in regions with a broad
array of intermittent and base-load resources might be able to
head off outages or other problems before a single lamp flickers
off, Ehrlich said.
“The big thing right now is predictive analytics,” he said. “If
I can analyze it and tell someone what’s about to happen, that’s
the star that everyone’s reaching for.”
ROSS is a freelance writer located in Brewster, Mass. He can be
reached at firstname.lastname@example.org. T H