Transcript Cold Climate Resource Assessment: Lessons

COLD CLIMATE RESOURCE ASSESSMENT:
LESSONS LEARNED
PHILIPPE C. PONTBRIAND
RES-Canada Technical Lead
Collaborators:
Eric Muszynski, Rory Curtis
2nd NOVEMBER 2010
Presentation Plan
• Introduction
– Canadian climate
– Impact of Cold Climate (CC) on project development
• Icing
– Icing type
– Icing prediction
– RES experience
• Cold climate measurement system
– Tower and instrumentation
– Portable power system
– Cost/Benefit analysis
• Cold climate and uncertainty
Introduction
Mean Temperature (°C)
• Lesson #1
C
anada
=
C
• Challenges
–
–
–
–
Very cold average temp
Extreme min. and max. temp
Average snow depth 0.5 to 2m
Icing over 6-7 months
old
Impact of CC on Project development
Tower Installation
Time constraints
Wind measurement
Icing on Instruments
Load on met towers
Maintenance
Site access
Cold Temp.
RFP
Financing
Requirements
Predicted Wind
Predicted Wind
Predicted Energy
Predicted Energy
Higher Risks
$/KWh Price
Equity vs Debt
Percent data capture (%)
Development
Winter 1
Winter 2
Winter 3
Icing and Wind Resource Assessment
Type of Icing
• Precipitation Icing
– Freezing rain
• Regional
• Not very common
• High impact
– Wet Snow
Worst enemies
• Not so common on site
• Varying adhesion
• In cloud Icing
– Rime ice
• Most common
• Local
• Strong adhesion
– Frost
Klock et al., 2001
• Not very common
Will there be icing at my site?
• Ice Map
– Freezing rain
• Public Maps : Env. Canada
• Very General
– Rime ice + Freezing Rain
• Few maps for Canada
• Not much research
Cortinas et al. 2004
Comeau et al. 2008
• Public Ice Measurement Data
Goodrich (Rosemount) Ice Sensor
• Almost none exists: Airports Env. Canada
• Often far from site
• Not always accurate
Altitude VS Icing in Canada
• 75 met towers operated by RES across Canada
– Full winter of data(October to May)
Above 550 meters AMSL:
– Anemometer height from 50 – 80m
Sensors affected > 10% of time
Hours of icing (Oct-May)
Mean hours of icing of unheated instrument vs Altitude
Altitude (m asl)
8
Cold Climate Measurement System
Cold climate measurement systems
Tubular 50-60m
Lattice 80m
Vaisala WAA252
NRG IceFree
+ Lower initial cost
- High maintenance cost
A2
HE-A1
A4
- More expensive
A1
HE-V1
A3
+ Low maintenance cost
V1
- Re-use value
A6
A5
+ Re-use value
V2
- More likely to collapse
- Longer to install
- No data @ Hub Height
+ Data @ Hub Height
?
Cold Climate Met Mast Life Cycle
Applies only to sites prone to icing
Assumption 2 :
2 maintenances per year per mast
Assumption 3:
For lattice: 1 tower out of 2 is refurbished.
Assumption 4:
For tubular: 1 tower out of 4 fails over lifetime
Cost Ratio
Assumption 1:
Cumulative Running Cost
Met Masts Summary
80 m lattice
• Good long term value
• Reduced shear uncertainty
Great Primary Mast
• Potential for better data availability
50 – 60 m tubular
• Good short term value
• Easier and faster to install
Great Secondary Mast
Autonomous Power System
Small Wind Turbine
RES Generators
Wind Turbines 1 kW:
RES Generator:
• Cheap: $10K
• Max of 2 heated instruments
• Not much flexibility
• Eco-Friendly
• Affected by trees
• Tend to freeze
• More: $35K
• Many instruments
• Flexible
1st generation
2nd generation
• Close to 100% availability
• Remote diagnostic tools
• Easy to deploy
RES Autonomous Power System Concept
Heating system concept
Impact of CC on Project development
Tower Installation
Time constraints
Wind measurement
Icing on Instruments
Load on met towers
Maintenance
Site access
Cold Temp.
RFP
Financing
Requirements
Predicted Wind
Predicted Wind
Predicted Energy
Predicted Energy
Higher Risks
$/KWh Price
Equity vs Debt
Percent data capture (%)
Development
Winter 1
Winter 2
Winter 3
Cold Climate and Uncertainty
Cold Climate and Uncertainty
•P50 is the amount of energy expected to be produced in an average year
• 50% chance lower. 50% chance higher than this value
•For many projects debt is sized on 1 year P99
• Annual energy production only expected to be as low as this (or lower) once every 100 years
• What is the effect of higher P99/P50 ratio?
• In other words: What is the value of lower uncertainty?
• Example: 100MW project, $135/MWh, 35% Cf , P99(1 Year) / P50 = 70%
• Increase P50 energy by 1% (Increase Cf to 35.35%),
• Power price will reduce by ~ $1.35/MWh
• Keep P50 at 35% Cf and increase P99(1 Year) / P50 ratio by 1% to 71%
• Power price will reduce by more than one might think
• 1% P99/P50 change has same value as around 0.5% to 0.7% change on P50
• Just an example treating P50 and P99 in isolation. Project financing dependent
Conclusions
Conclusions:
•First of All …
• Never underestimate the challenges of Canada’s cold climate
•Icing
•Not much research available to help characterize a Canadian site
•Information about icing can be extracted from simple parameters like altitude
•Towers and Instrumentation
•Tower and instrument type need to be chosen carefully
• Heating the instruments with the proper power system is a must
•Cost of Uncertainty
• De-icing and maintenance of instruments are key to reducing uncertainty