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P E R S P E C T I V E
46 ● Renewable Watch ● December 2014
M
uch has been written about the
capabilities of big data and analyt-
ics to transform industries – from
retail to railroads and hospitality to health
care. There are many prominent examples
at the consumer level, but the industrial
sector is also catching up quickly.
The consumer internet helped people
across the globe interact with each other
in ways never imagined before, and those
connections created enormous amounts
of data. In the same way, when billions of
machines connect with each other
through the industrial internet, an analysis
of the resulting data could unlock consid-
erable value for industrial operations.
Using data and analytics for wind power
The industrial internet is transforming the
way wind power is generated and dis-
patched. Today, wind turbines generate a
substantial amount of data. For example,
GE continuously monitors a fleet of more
than 19,000 turbines that generate approx-
imately 1 petabyte of data every year. The
industrial internet uses the power of data
and analytics to drive informed decisions
for customer outcomes, including:
Better predictability: Through the con-
tinuous monitoring of turbines from the
supervisory control and data acquisition
system and the remote operations cen-
tre, along with advanced predictive
analytics to warn of impending failures
much before the occurrence of a cata-
strophic event.
Higher productivity: From effective dis-
patch of service personnel, enabled by
digitised workflows, hand-held devices,
and integrated asset and inventory
management systems; as well as cen-
tralised analytics platforms that provide
a single-window view of multiple wind
farm operations.
Improved compliance: In line with reg-
ulatory requirements such as forecast-
ing and scheduling for the Renewable
Regulatory Fund in India, or other grid
integration requirements through inte-
grated forecasting, wind farm control
systems and energy storage solutions.
The power of the industrial internet does
not stop there. Using a combination of
software applications and hardware modi-
fications, it also drives turbine perform-
ance upgrades that enhance project life
cycle economics.
Performance upgrades for higher AEP
While wind turbines are designed to suit a
region’s wind conditions, as technologies
Harnessing the industrial internet for wind power
Beyond Big Data
By MMilesh GGogad, SSenior PProduct MManager, GGE RRenewables
GE’s industrial iinternet vvision ffor wwind ppower
P E R S P E C T I V E
December 2014 ● Renewable Watch ● 47
evolve with time, the turbines in operation
can be tuned to generate the maximum
energy output on the basis of current wind
conditions at a specific farm site. These
modifications require an in-depth analysis
of the operating parameters of the turbine,
collected over a statistically relevant
period, along with knowledge about the
turbine’s design loads.
The turbine’s performance can be im-
proved through controller tuning, changing
the control strategy (such as increasing the
rated power and/or speed of the machine),
adding hardware enhancements (such as
vortex generators) to improve blade aero-
dynamics, using real-time turbine data to
make smarter operating decisions, or a
combination of these technologies. By
combining one or more of these modifica-
tions, operators can achieve an increase in
the annual energy production (AEP).
As much as turbine performance up-
grades help improve wind farm operator
bottom lines, a random change in the tur-
bine’s control parameters or ratings could
be counterproductive. After all, wind farm
developers have to operate the asset for
20 years. The following is a short checklist
of what to watch out for before signing up
for such performance upgrades:
Native turbine technology: The control
parameters of a wind turbine are inter-
related. Any tweak in one of the para-
meters to improve performance has a
direct impact on other parameters. Like-
wise each turbine model has a different
design margin (for loads, for example)
which it can withstand. A deep under-
standing of the interrelationships between
various parameters and the turbine’s
design limits is essential for safe opera-
tion of the turbine over its life.
Integration with farm systems: A tight inte-
gration of the turbine hardware and its
subsystems with the software applica-
tions referred to earlier ensures a seam-
less, enriched user experience.
Outcome-based commercial models: The
industrial internet enables outcome-driven
commercial models in wind power, with lit-
tle or no upfront investment from develop-
ers. A financial model based on “validat-
ed” performance gains helps reduce the
risk for wind farm developers, because
they work collaboratively with the manu-
facturer and pay only after the added per-
formance is verified.
Conclusion
As the consumer and the industrial
worlds converge, wind farm operators
are increasingly demanding the same
level of experience and outcomes that
they receive from their personal comput-
ing devices and applications. The indus-
trial internet moves us closer to that goal,
and helps turn productivity improve-
ments into performance enhancements.
Any improvements that can be gained
from big data and analytics are only as
good as the institutional knowledge
behind them. Operators must ensure
that their efforts are backed by a solid
understanding of the native technology
of the turbine, a seamless integration
with other systems, and outcome-based
commercial models. ■
GE offers a service platform called PowerUp that results in an AEP gain of up to 5 per cent,
taking into account environmental conditions. It is helping increase the AEP of the fleets of
some leading renewable power producers such as E.ON, EDP Renewables, First Wind,
ENERTRAG AG and the Monsson Group.
PowerUp services are a part of GE’s Brilliant Wind Platform and Predictivity solutions,
which utilise the industrial internet to analyse tens of thousands of data points on a wind farm
every second, driving higher output and tailoring the wind turbine to its wind site conditions.
It adjusts performance dials such as speed, torque, pitch, aerodynamics and turbine con-
trols, with the goal of maximising the power output of a wind farm. To ensure transparency,
a GE software program performs a complete before and after PowerUp wind farm power
performance analysis, validating the performance improvement.
The service has secured more than 1,000 turbines under contract with a potential 194
GWh of additional energy per year. E.ON Climate & Renewables, a leading wind energy
developer with more than 10 GW of capacity, enrolled 283 of its 469 GE 1.5-77 wind turbines
in the PowerUp programme. The service achieved up to 4 per cent more power output, rep-
resenting 40 GWh of additional energy production. Once all its 469 turbines are validated,
E.ON could benefit from a projected increase of 87 GWh of additional energy production
across all turbines or the equivalent of 19 additional GE wind turbines to its fleet, based on
performance extrapolations.
GE’s PowerUp service platform
GE’s PowerUp services to improve AEP by up to 5 per cent

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Renewable Watch Magazine - Beyond Big Data

  • 1. P E R S P E C T I V E 46 ● Renewable Watch ● December 2014 M uch has been written about the capabilities of big data and analyt- ics to transform industries – from retail to railroads and hospitality to health care. There are many prominent examples at the consumer level, but the industrial sector is also catching up quickly. The consumer internet helped people across the globe interact with each other in ways never imagined before, and those connections created enormous amounts of data. In the same way, when billions of machines connect with each other through the industrial internet, an analysis of the resulting data could unlock consid- erable value for industrial operations. Using data and analytics for wind power The industrial internet is transforming the way wind power is generated and dis- patched. Today, wind turbines generate a substantial amount of data. For example, GE continuously monitors a fleet of more than 19,000 turbines that generate approx- imately 1 petabyte of data every year. The industrial internet uses the power of data and analytics to drive informed decisions for customer outcomes, including: Better predictability: Through the con- tinuous monitoring of turbines from the supervisory control and data acquisition system and the remote operations cen- tre, along with advanced predictive analytics to warn of impending failures much before the occurrence of a cata- strophic event. Higher productivity: From effective dis- patch of service personnel, enabled by digitised workflows, hand-held devices, and integrated asset and inventory management systems; as well as cen- tralised analytics platforms that provide a single-window view of multiple wind farm operations. Improved compliance: In line with reg- ulatory requirements such as forecast- ing and scheduling for the Renewable Regulatory Fund in India, or other grid integration requirements through inte- grated forecasting, wind farm control systems and energy storage solutions. The power of the industrial internet does not stop there. Using a combination of software applications and hardware modi- fications, it also drives turbine perform- ance upgrades that enhance project life cycle economics. Performance upgrades for higher AEP While wind turbines are designed to suit a region’s wind conditions, as technologies Harnessing the industrial internet for wind power Beyond Big Data By MMilesh GGogad, SSenior PProduct MManager, GGE RRenewables GE’s industrial iinternet vvision ffor wwind ppower
  • 2. P E R S P E C T I V E December 2014 ● Renewable Watch ● 47 evolve with time, the turbines in operation can be tuned to generate the maximum energy output on the basis of current wind conditions at a specific farm site. These modifications require an in-depth analysis of the operating parameters of the turbine, collected over a statistically relevant period, along with knowledge about the turbine’s design loads. The turbine’s performance can be im- proved through controller tuning, changing the control strategy (such as increasing the rated power and/or speed of the machine), adding hardware enhancements (such as vortex generators) to improve blade aero- dynamics, using real-time turbine data to make smarter operating decisions, or a combination of these technologies. By combining one or more of these modifica- tions, operators can achieve an increase in the annual energy production (AEP). As much as turbine performance up- grades help improve wind farm operator bottom lines, a random change in the tur- bine’s control parameters or ratings could be counterproductive. After all, wind farm developers have to operate the asset for 20 years. The following is a short checklist of what to watch out for before signing up for such performance upgrades: Native turbine technology: The control parameters of a wind turbine are inter- related. Any tweak in one of the para- meters to improve performance has a direct impact on other parameters. Like- wise each turbine model has a different design margin (for loads, for example) which it can withstand. A deep under- standing of the interrelationships between various parameters and the turbine’s design limits is essential for safe opera- tion of the turbine over its life. Integration with farm systems: A tight inte- gration of the turbine hardware and its subsystems with the software applica- tions referred to earlier ensures a seam- less, enriched user experience. Outcome-based commercial models: The industrial internet enables outcome-driven commercial models in wind power, with lit- tle or no upfront investment from develop- ers. A financial model based on “validat- ed” performance gains helps reduce the risk for wind farm developers, because they work collaboratively with the manu- facturer and pay only after the added per- formance is verified. Conclusion As the consumer and the industrial worlds converge, wind farm operators are increasingly demanding the same level of experience and outcomes that they receive from their personal comput- ing devices and applications. The indus- trial internet moves us closer to that goal, and helps turn productivity improve- ments into performance enhancements. Any improvements that can be gained from big data and analytics are only as good as the institutional knowledge behind them. Operators must ensure that their efforts are backed by a solid understanding of the native technology of the turbine, a seamless integration with other systems, and outcome-based commercial models. ■ GE offers a service platform called PowerUp that results in an AEP gain of up to 5 per cent, taking into account environmental conditions. It is helping increase the AEP of the fleets of some leading renewable power producers such as E.ON, EDP Renewables, First Wind, ENERTRAG AG and the Monsson Group. PowerUp services are a part of GE’s Brilliant Wind Platform and Predictivity solutions, which utilise the industrial internet to analyse tens of thousands of data points on a wind farm every second, driving higher output and tailoring the wind turbine to its wind site conditions. It adjusts performance dials such as speed, torque, pitch, aerodynamics and turbine con- trols, with the goal of maximising the power output of a wind farm. To ensure transparency, a GE software program performs a complete before and after PowerUp wind farm power performance analysis, validating the performance improvement. The service has secured more than 1,000 turbines under contract with a potential 194 GWh of additional energy per year. E.ON Climate & Renewables, a leading wind energy developer with more than 10 GW of capacity, enrolled 283 of its 469 GE 1.5-77 wind turbines in the PowerUp programme. The service achieved up to 4 per cent more power output, rep- resenting 40 GWh of additional energy production. Once all its 469 turbines are validated, E.ON could benefit from a projected increase of 87 GWh of additional energy production across all turbines or the equivalent of 19 additional GE wind turbines to its fleet, based on performance extrapolations. GE’s PowerUp service platform GE’s PowerUp services to improve AEP by up to 5 per cent