The economics of reducing the cost of energy by 13% revenues

The Economics of Using Digitalization to Reduce
the Cost of Energy by 13% of Revenues

SentientScienceCorp.-Proprietary/PrivateLevel1
Host
Natalie Hils
Director, Revenue Marketing
nhils@sentientscience.com
+1 716.807.8655
Webinar: The Economics of Using Digitalization to Reduce the Cost of Energy by 13% of Revenues

Webinar Instructions

© 2016 Sentient Science Corporation – Confidential & Proprietary
About Sentient Science
Our Pedigree & Awards/Recognition
2001-2016
51 SBIR Awards
16 Phase II Projects
$15M+ SBIR Funding
2010
NASA Validates
DigitalClone®
2014
Tibbett's Award
Best SBIR Program
April 2016
2016 Bloomberg
New Pioneer Award
October 2017
2017 Frost & Sullivan
New Product Innovation
Award

Sentient Science Data Fusion - Differentiation
Material Science Models
Data Science Models
Data Fusion
MODELS
12-18 months
COMPONENT
REMOVAL
DAMAGE
INITIATION
3 yrs Life 5 yrs Life +
time
Portfolio Manager, Purchasing Manager
Asset
Watchlists
Risk
Forecasts
Component
Watchlists
Site Manager
Asset
Watchlists
Risk Manager
Risk
Forecasts
VALUE

Sentient Science Customers

© 2016 Sentient Science Corporation – Confidential & Proprietary
WIND TURBINE MODELS COMPLETE OR UNDER CONTRACT
Acciona
Windpower
AW 1500 (1.5MW) AW3000 (3.0MW)
Alstom Ecotechnia 74,80 (1.6MW)
Bonus B41, B44 (600kW), B62 (1.3MW)
Clipper 2.5MW
Gamesa
Made AE 30 (330k), G42, G47 (660k), Made AE 46 (660k), G52, G5X
(850k), G87, G8X, G90 (2MW)
GE
1.5, 1.5S, 1.5SLE (1.5MW), 1.6/1.7-100, 103 1.6SLE (1.6MW), 1.85
Repower (1.85MW),
2.0 (2MW), 2.3MW
Goldwind G48-759 (750k)
MHI Vestas V164 (2.4MW)
Mitsubishi MWT-1000-57 (1MW)
Neg Micon NM44-48 (600k), NM52 (900k)
Nordex N60 (1.3MW), N80 (2.4MW), N90 (2.5MW)
Senvion 2XM (2MW), MM92 (2.05MW)
Siemens 2.3MW, 3.6MW
Sinovel 1.5MW
Suzlon S88 (2.1MW)
United Power U97 (2MW)
Vestas
V47 (660k), V80, V90, V93/G42, V100 (1.8MW), V82 (1.65MW), V117
(3.3MW)
GEARBOXES COMPLETE OR UNDER CONTRACT
BaoChi GD1663B
Bosch
Clipper Quantumdrive
Dalian PPSX129
Echesa GE2000PL, PE477V, PE88-A, GE700PL, GE850PL
Eickhoff CPKHZ-195
Fellar
TPH3-1600HN, TPH3-1500, TPH3-1080V-1080V/1,
TPH3-1100G/1- 1100G
Metso/Moventas
PLH3-8X61, S3GHD-500X, PLH1100, PLH2900, S3GHD-506X,
PLH-309X1G, 310X1G, 312X1G
Nanjing FDM-00R8, FDMD, FDMF, FDM2, FD835-01R7
Winergy/Flender
PEAB4407, PZAB3535, PEAS4375.x, PEAS4280.x, PPSX129,
PEAS4280.1, 4411, 4419, PEAB4410.2, PEAB4431, PZA3505,
PEAC4300.x, PEAB4420
Sentient’s Digital Library of
Wind Turbine and GBX Models

International Energy Agency 2017: Value of Digitalization
Optimize
O&M
Costs
1. IEA claims that the overall savings could be in the
order of USD 80 billion per year from 2016-40.
2. One of the most important benefits of digitalization
is extending the operational lifetime of power
plants and network components, through
improved maintenance and reduced physical
stresses on the equipment.
3. If the lifetime of all the power assets in the world
were extended by five years, close to USD 1.3
trillion of cumulative investment could be deferred
over 2016-40. On average, investment in power
plants would be reduced by USD 34 billion per
year and that in networks by USD 20 billion per
year.
Increase
Network
Efficiencies
Reduce
Unplanned
Outages
Life Extension
of Assets
Improved
O&M
Source: http://www.iea.org/digital/#section-4

New
Development
• Win new deals
• Competitive PPA biding
• Buy on Life & Price
• Optimize suppler choices
Business Strategy
• Optimal Governance by digitizing wind fleets
• Integration with existing MAXIMO and other IT systems
• Optimize Key Performance Indicators to lower Cost of Energy
• Benchmark performance against industry competitors
Operations Management
• Lower the cost of asset operations
• Reduce technical visits due to bundling & false alarms
• Reduce costs from scheduling technician time and
equipment
Asset Management
• 18 month rolling budgets and forecasts
• Avoid down-tower rebuilds with increased up-tower
replacements
• Reduce mobilization cost by bundling crane visits
• Avoid downtime with inventory available
Risk Management
• Reduce insurance and extended warranty
costs
• Reduce annual gearbox replacements with
preventative O&M recommendations
• Reduce long-term gearbox O&M cost with
“right first time” procurement
• Reduce insurance premium from risk
management
Supply Chain
• Improve terms and costs with key suppliers
• Reduce risk of exceeding O&M budgeting
• Reduce inventory storage required to mitigate failure risk
• Reduce unit cost of gearbox purchases with long-term
agreements
DigitalClone®
Reducing COE by
13% of Revenues
6 Business Areas to Reduce Costs with Digitalization

Presenter
Keith Vergien
Vice President, Energy Operations
kvergien@sentientscience.com

Savings of Revenue
2018 2019 2020 2021 2022
Total Assets under DCL Contract 200 600 1000 1400 1800
Avergae MW - Per Asset 1.56 1.56 1.56 1.56 1.56
Total MW 312 936 1560 2184 2808
Price per MWh - Power Purchase
Agreement (PPA)
$ 36.86 $ 36.86 $ 36.86 $ 36.86 $ 36.86
Price per MWh from Production Tax
Credit (PTC)
$ 24.25 $ 24.25 $ 24.25 $ 24.25 $ 24.25
Average Capacity Factor 38% 38% 38% 38% 38%
Average Turbine Availability 96.9% 96.9% 96.9% 96.9% 96.9%
Per Turbine - Daily Production
Revenue
$ 848 $ 848 $ 848 $ 848 $ 848
Per Turbine - Annual Revenue $ 309,525 $ 309,525 $ 309,525 $ 309,525 $ 309,525
Total Assets - Revenue $ 61,905,067 $ 185,715,202 $309,525,337 $ 433,335,471 $ 557,145,606
5% Savings in O&M, per IEA org. $ 3,095,253 $ 9,285,760 $ 15,476,267 $ 21,666,774 $ 27,857,280
13% Savings - Sentient Science DCL
through all business units
$ 8,047,659 $ 24,142,976 $ 40,238,294 $ 56,333,611 $ 72,428,929
Savings captured in BVA $ 1,060,151 $ 3,802,679 $ 7,486,222 $ 12,247,866 $ 18,228,702
% of Savings Capture, per IEA org vs
BVA
34.3% 41.0% 48.4% 56.5% 65.4%
DESCRIPTION
PRODUCTION&FINANCIAL

Business Value Assessment Summary
Year 2018 2019 2020 2021 2022
TotalAssets in DCL 200 600 1000 1400 1800
Total Savings Per Deployment 1,060,151$ 3,802,679$ 7,486,222$ 12,247,866$ 18,228,702$
Savings perAsset 5,301$ 6,338$ 7,486$ 8,748$ 10,127$
Savings perMW 2,718$ 3,250$ 3,839$ 4,486$ 5,193$
TotalFleetDigitalClone Live Price: 195,000$ 585,000$ 975,000$ 1,365,000$ 1,755,000$
ROI Ratio: 4.4 5.5 6.7 8.0 9.4
Selecting "Best" LifeX Action: Choosing the correct action
to avoid Future Cost of "Right First Time" Replacement
(Matching correct component to Asset age,align remaining
useful life)
$ 491,216 $ 1,600,284 $ 2,882,258 $ 4,342,100 $ 5,984,880
Short-term Watchlist(0-12mo): Early Detection priorto
consequential damage,beyond operatorcurrent
capabilities
535,500$ 2,076,452$ 4,347,790$ 7,477,751$ 11,598,868$
Short-term Watchlist(0-12mo): LostEnergy Per Asset -
Reduce Downtime,Ensure Resource is Available forChange-
Outs - (Manpower, Parts,Tooling,Equipment)
33,435$ 125,943$ 256,174$ 428,015$ 644,955$
Example of Value Statements
Example:

Business Value Assessment – Assumptions
2018 2019 2020 2021 2022
Total Assets under DCL Contract 200 600 1000 1400 1800
Avergae MW - Per Asset 1.95 1.95 1.95 1.95 1.95
Average Wind Turbine Capacity Factor 45% 45% 45% 45% 45%
Price per MWh - Power Purchase Agreement (PPA) $ 38.00 $ 38.00 $ 38.00 $ 38.00 $ 38.00
Price per MWh from Production Tax Credit (PTC) $ 25.00 $ 25.00 $ 25.00 $ 25.00 $ 25.00
Cost of Capital 5.50% 5.50% 5.50% 5.50% 5.50%
Average Per Event Downtime (Days) - Up-tower 4 4 4 4 4
Average Per Event Downtime (Days) - Full GBX Replacement 20 20 20 20 20
Average Annual GBX Failure Rates 7.5% 7.4% 7.2% 7.1% 6.9%
Up-Tower Repair Frequency 3.0% 2.9% 2.9% 2.8% 2.8%
Complete GBX Replacement Frequency 4.5% 4.4% 4.3% 4.2% 4.2%
Average Per Event Up-Tower Repair Costs $ 10,000 $ 10,500 $ 11,025 $ 11,576 $ 12,155
Average Cost of GBX, including manpower and crane
mobilization $ 350,000 $ 360,500 $ 371,315 $ 382,454 $ 393,928
Average Per Asset, Potential Savings $ 340,000 $ 350,000 $ 360,290 $ 370,878 $ 381,773
% of increased uptower repairs to downtower refurbishment 35% 41% 47% 52% 58%
Sentient Capture Rate 50% 55% 60% 65% 70%
GEARBOXEVENT
PRODUCTION&
FINANCIAL
DESCRIPTION
Example:

Long Term Service Agreement – Business Value
Year 2028 2029 2030 2031 2032
# of Assets underLong term service agreement LTSA 330 330 330
LTSA Total Cost - Today (per asset peryear) $ 45,000 $ 54,000 $ 64,800
LTSA Estimated costs today peryear $ 14,850,000 $ 17,820,000 $ 21,384,000
LTSA Estimated costs at time of renewal peryear $ 17,077,500 $ 20,493,000 $ 24,591,600
NPV LTSA Cost years 10-20 $ 80,955,469 $ 97,146,563 $ 116,575,875
# of Assets under Long term service agreement LTSA renewal 330 330 330
% of LTSA negotiated savings by having historical Data and
estimated forward risk
10.0% 10.0% 10.0%
Estimated LTSA negotiated savings by having historical Data and
estimated forward risk
$ 8,095,547 $ 9,714,656 $ 11,657,588
Weighted Average Cost of Capital 5% 5% 5%
Cost of Monitoring Fleet per year- (Digital Clone) $ 321,750 $ 321,750 $ 321,750
NPV Cost of Monitoring Fleet over yrs 1-10 $ 2,608,692 $ 2,608,692 $ 2,608,692
Total Cost Savings over yrs 1-10 $ 5,486,855 $ 7,105,965 $ 9,048,896
Annual Cost Savings 548,686$ 710,596$ 904,890$
Total Cost Savings 21,641,716$
Medium/Long TermWatchlist (0-48mo): Cost Savings - Long Term Service Agreement Negotiation
Align corporate objectives to bid or manage LTSA agreementsExample:

The Economics of Using Digitalization to Reduce the COE by 13% of Revenues
01
Understand the current
health of your asset to
reduce planned and
unplanned maintenance
activities.
02
Asset Management
Optimize Asset Portfolio to
reduce costs and increase
AEP.
03
Supply Chain Management
Improved planning and
scheduling for critical part-
replacements and long-term
agreements with suppliers
for major systems within the
turbine.
04
Risk Management
Reduce extended warranty
costs and insurance
premiums.

Our primary business goal is LIFE EXTENSION, In order to accomplish this our software focuses
on three areas of inter-related value:
Inter-related Value:
1. Verify Asset Life State... Identification of damage on units with no additional sensoring (e.g.:
CMS, Oil sensors, …). Helps primarily O&M. Technological approach: Data Science & Material
Science.
2. Long Term Forecasting Term of <36 Months helps primarily Asset Management, Procurement
& Planning. Term of >36 Months helps primarily Risk & Insurance Management.
3. Life comparisons using computational testing – Leverage computational testing to support
physical testing (vs. year long testing on limited samples) to greatly improve understanding of
sensitivity of life to loading, mechanical design and material quality factors.
Life Extension to Reduce the Cost of Energy

01
Operations
Management
Understand the current health of your asset to
reduce planned and unplanned maintenance
activities.

Case Study: Operations Management
By evaluating the lost energy per asset, the operator was able to improve efficiency of manpower
by ensuring the availability of the replacement and the right tools and equipment were in place
when the repairs were done up-tower. Across a fleet, annual savings of $600,000 to $1.9 million
can be achieved with early detection prior to consequential damage and through the optimization
of maintenance activities, man power efficiency and improved safety of technicians.
Business Challenge: Correctives that occur in high wind
conditions have a significant impact on use of
operational manpower
Component(s): Intermediate Pinion Bearing
Case Study: In visual representation to the right, an
intermediate pinion bearing with a predicted life of 16.6
years showed signs of damage. It was recommended that
the additive solution be applied to the bearing and gear
to extend life until an up-tower replacement could be
performed during a low wind productivity period to
optimize return on investment (ROI).

#1 Value for Operations Management
 Reduced planned and unplanned maintenance activities, work-orders and
costs
 Gearboxes projected to fail that are not on the current watchlist
 Identification of gearboxes with damage under warranty that can be used for
post warranty negotiations
 Improve failure prognostics reporting over existing internal capabilities
 Improve quality and consistency of failure reporting and action
 Calculated remaining useful life of a gearbox based on uprating
 List of critical subcomponents causing a reduction in life and replacement
options
 Strengthen the accuracy of your watch list(s)
 Logistics and service effectiveness
 Manage for serviceability
 Crane & service optimization
 BOM management
Operations
Management
$ 1 MW/hr.

Asset Management
Optimize Asset Portfolio to reduce costs and
increase Annualized Energy Production (AEP).
02

Case Study: Asset Management
Business Challenge: Optimize Asset Portfolio to reduce cost and increase AEP
Component(s): High Speed Shaft Bearing, Low Speed Ring Gear
Case Study Description: Sentient’s DigitalClone software accurately predicted damage to the
inbound High-Speed Shaft Bearing (HSS) and Planet Stage, Low Speed Ring Gear (LSR-GR). Both were
expected to fail at 24 months and 36 months, respectively. If the operator allowed the asset to
continue operation with no repair, complete gearbox replacement would have been required.
Therefore a defined savings of ~$260,000 was recognized.
The OEM recommended replacing the HSS bearing for 12 months additional life and to push the full
gearbox replacement out 24-months’ time. The cost would have been ~$6,000 upfront, for a savings
of $254,000 in the current budget year. However, within 2 years the impact of the ring gear failure
would be at the surface, and a full swap out of the gearbox would be needed.
Using computational testing, the software demonstrated seven different options of asset actions,
each with different ROIs. It was found that the most valuable action would be to replace the HSS
bearing with a higher quality performance bearing and to apply a surface treatment for the life
extension of the ring-gear bearing. A combined cost of ~$40,000 and life extension of an additional
36 months, predicted a Net Present Value (NPV) of $221,000 savings.

#2 Value for Asset Management
 Life extension options for both in and out of warranty assets - including
repowered assets
 Multi-year rolling O&M forecasting by assets, site, fleet and energy production
 Impact of uprating
 Multiyear subcomponent forecast & budgeting and ROI calculations based on
3D watchlist
 Supplier and component optimization for longer life
 Bulk buying agreement based on multi-year component replacement forecasts
 Reduced planned and unplanned maintenance activities, work-orders and costs
 Asset Comparison (Vendor selection assistance ) - Buy on Life & price to
purchase replacements with higest ROI
 Buy vs “Power by the Hour” options
Asset
Management
$ 4 MW/hr.

Supply Chain
Management
Improved planning and scheduling for critical part-
replacements and long-term agreements with
suppliers for major systems within the turbine.
03

Case Study: Supply Chain Management
Business Challenge: Supply chain optimization, improved efficiencies and
planning directly impacts the improvement of risk management of an
organization.
Component(s): Gearbox Assemblies
Case Study: DigitalClone evaluated more than 100 field gearboxes from a
universal OEM and uncovered a risk of a poor-quality material from
bearings manufactured in a specific year. It was recommended that those
bearings be exchanged with an alternative option to prevent future high
failure rates of this specific gearbox type in the fleet. A supplier trade off
study was completed to assess the impact of varying supplier choices.
In another example, DigitalClone demonstrated the return on investment
of picking gearbox OEMs for future development. Based on the failure
risks and estimated costs, Figure 2 shows supplier 3 is optimal with a
failure rate of less than 50% over 20 years as opposed to supplier 4, which
shows a 98% failure rate over 20 years. The financial implications of
choosing supplier 4 would be detrimental to the profitability of the site.
Assembly/System
Lifecycle Prediction
Materials
Figure 2
Component
Lifecycle Prediction

#3 Value for Supply Chain Management
 Multi-year inventory forecasts for major and minor
correctives based on failure rates
 Better T&Cs with Suppliers
 Reduce variability between suppliers
 Know the life of the supplier offering
 Reduced inventory and supply carrying costs
 less inventory, JIT, shorter lead times
 Place inventory where and when needed
 Reduce T&C based on long term forecasting
 Decide whether to Increase or decrease number of suppliers
 Definition of serial failure of subcomponents out of warranty
 Work with suppliers and remanufacturing resources to
improve fielded products – Additives/Coatings
Supply
Chain
$ 1 MW/hr.

Risk Management
Reduce extended warranty costs and insurance
premiums.
04

Risk Management
Business Challenge: Loss of rejected insurance claims through additional requirements from
insurance carrier.
Component(s): Gearbox Assemblies
Case Study Description: Root cause analysis becomes important to understand when damage
initiated, why the failure occurred, and how to evaluate life extension actions that mitigate repeat
failures in the future.
Insurance providers have rejected insurance claims in the past when inadequate data is provided
that supports the root cause of the failure. When a claim is rejected the operator is required to pay
the full amount of the exchange, which can total more than $350,000 for each gearbox
replacement as opposed to a $100,000 deductible. A customer could see up to 5% or more of their
insurance claims rejected in any given year. With materials science, this risk could be eliminated,
saving on average $20,000 per failure, saving on average between $125,000 to $450,000 annually
as additional assets come online for digital monitoring.

#4 Value for Risk Management
 Reduced extended warranty costs
 Failure rates and data used to reduce or isolate assets that require coverage
 Reducing litigation/arbitration costs
 Reduced insurance premiums
 Insurance on components vs. blanket coverage
 Better financing terms based on better knowledge of fleet
health and longevity
 Improved prediction ability with a better insight into long term health
 Serial failure of components under warranty
 RCA Reports to identify who pays
 Life extension beyond Proforma
Risk
Management
$ 3 MW/hr.

Data Science – Sentient WayOperationalizing the selection of "BEST" Life Extension Option for an Asset
DigitalClone LifeX Actions enable
life extension decisions based on
optimal financial returns
Life Extension
Asset Actions
Operating Conditions,
Maintenance Events, &
Configuration
Asset Life
State
Informed
LifeX
Decision
Probabilistic
Financial
Forecasts
Site
Financials
Risk-Based
Scenario
Assessments
Supplier
Options
Customer Factors
for Decision-
making

BLADES
Vision:
• Smart Drone inspections
• Time to next damage state
• Life predictions
Today:
• Life predictions: initial models deployed in
December w/ Bladena. Validation in progress.
PITCH BEARINGS
Vision:
• Short Term Predictions (0-12mos)
• Long Term Predictions (>12mos)
• Life Extension Recommendations
Today:
• Model development in progress [Internal]
GEARBOXES + OIL SENSOR
Vision:
• DCL gearbox lifing to guide strategic
placement of oil sensors
• Integration to DigitalClone to improve short
term predictions (Time to next damage state)
Today:
• Static Oil report data ingested in LifeX State
GENERATORS
Vision:
• Short Term Predictions (0-12mos)
• Long Term Predictions (>12mos)
• Life Extension Recommendations
Today:
• Model development in progress w/ Ingeteam
DigitalClone® Platform: Expanding component catalogue

Business Value Assessment Summary
Year 2018 2019 2020 2021 2022
TotalAssets in DCL 200 600 1000 1400 1800
Total Savings Per Deployment 1,060,151$ 3,802,679$ 7,486,222$ 12,247,866$ 18,228,702$
Savings perAsset 5,301$ 6,338$ 7,486$ 8,748$ 10,127$
Savings perMW 2,718$ 3,250$ 3,839$ 4,486$ 5,193$
TotalFleetDigitalClone Live Price: 195,000$ 585,000$ 975,000$ 1,365,000$ 1,755,000$
ROI Ratio: 4.4 5.5 6.7 8.0 9.4
Selecting "Best" LifeX Action: Choosing the correct action
to avoid Future Cost of "Right First Time" Replacement
(Matching correct component to Asset age,align remaining
useful life)
$ 491,216 $ 1,600,284 $ 2,882,258 $ 4,342,100 $ 5,984,880
Short-term Watchlist(0-12mo): Early Detection priorto
consequential damage,beyond operatorcurrent
capabilities
535,500$ 2,076,452$ 4,347,790$ 7,477,751$ 11,598,868$
Short-term Watchlist(0-12mo): LostEnergy Per Asset -
Reduce Downtime,Ensure Resource is Available forChange-
Outs - (Manpower, Parts,Tooling,Equipment)
33,435$ 125,943$ 256,174$ 428,015$ 644,955$
Example of Value Statements

Business Value Assessment – Detailed Value Statements
Rank Defined Value Statement Yr1 (Start) Yr2 Yr3 Yr4 Yr5 Category
1
Selecting "Best" Asset Action: Choosing the correct
asset action to avoid Future Cost of "Right First Time"
Replacement (Matching correct component to Asset
age,align remaining useful life)
$ 308,108 $ 1,456,288 $ 3,371,029 $ 3,218,663 $ 3,309,789
Asset Management
2
Short-term Watchlist (0-12mo): Early Detection prior
to consequential damage,beyond operator current
capabilities
$ 566,010 $ 2,198,212 $ 4,047,254 $ 3,143,653 $ 2,170,479
Asset Management
3
Medium Term Forecast (12-36mo): Reduction in
major component storage costs and increased cash
flow through improved forecasting 6-12mo
$ 53,031 $ 347,756 $ 998,520 $ 1,206,195 $ 1,394,464
Supply Chain
4
Medium Term Forecast (12-36mo): Savings from
Improved planning for critical parts replacement -
Long term agreements with suppliers, based on
forecast
$ 95,043 $ 499,533 $ 1,279,606 $ 1,459,516 $ 1,650,316
Supply Chain
5
Short-term Watchlist (0-12mo): Lost Energy Per Asset
- Reduce Downtime, Ensure Resource is Available for
Change-Outs - (Manpower,Parts,Tooling,Equipment)
$ 20,276 $ 103,621 $ 258,045 $ 286,092 $ 314,413
6
RCA: Increase Warranty Claim payout through root
cause analysis
$ 77,826 $ 362,529 $ 833,937 $ 863,250 $ 893,594
Risk Management
7
Reporting Functionality - Automated reporting,
repository for damage class,BOM management,DCL
platform
$ 27,091 $ 154,139 $ 309,439 $ 313,840 $ 318,336
Asset Management
MB Total Main Bearing Savings - Five Value Statements $ 35,034 $ 157,897 $ 374,840 $ 379,242 $ 401,682 Operations Management
Gearbox & Main Bearing Savings 1,182,420 5,279,975 11,472,671 10,870,451 10,453,073
Gen Total Generator Savings $ 80,263 $ 504,951 $ 1,221,570 $ 1,302,161 $ 1,398,174 Business Strategy
PB Total Pitch Bearing Savings $ 506,968 $ 4,049,019 $ 10,745,695 $ 12,403,885 $ 14,207,987 Business Strategy

Questions?
Natalie Hils
Director, Revenue Marketing
nhils@sentientscience.com
+1 716.807.8655
Keith Vergien
Vice President, Energy Operations
kvergien@sentientscience.com

Meet the Team!
1. September 25-28: WindEnergy Hamburg Global Summit I Hamburg, Germany
2. October 1-2: AWEA Finance & Investment Seminar – East I New York, NY
3. October 5: AWEA Finance & Investment Seminar – West I San Francisco, CA
4. October 16-17: AWEA Offshore Symposium I Washington, DC
5. October 17-19: China Windpower I Beijing, China
6. November 13-15: AWEA Fall Symposium I Colorado Springs, CO

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Editor's Notes