COLD CLIMATE RESOURCE ASSESSMENT:LESSONS LEARNED

PHILIPPE C. PONTBRIANDRES-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

• Lesson #1

• Challenges

– Very cold average temp– Extreme min. and max. temp– Average snow depth 0.5 to 2m – Icing over 6-7 months

C = Canada old

Mean Temperature (°C)

Impact of CC on Project development

Tower InstallationTime constraints

Wind measurementIcing on InstrumentsLoad on met towers

MaintenanceSite accessCold Temp.

Development RFP Financing

Requirements

Predicted Wind

Predicted Energy

$/KWh Price

Predicted Wind

Predicted Energy

Higher Risks

Equity vs Debt

Winter 1 Winter 2 Winter 3

Pe

rce

nt

da

ta c

ap

ture

(%

)

Icing and Wind Resource Assessment

Type of Icing

• Precipitation Icing– Freezing rain

• Regional• Not very common • High impact

– Wet Snow • Not so common on site• Varying adhesion

• In cloud Icing– Rime ice

• Most common• Local• Strong adhesion

– Frost • Not very common

Worst enemies

Klock et al., 2001

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• Almost none exists: Airports Env. Canada• Often far from site• Not always accurate

Goodrich (Rosemount) Ice Sensor

Altitude (m asl) 8

Altitude VS Icing in Canada

• 75 met towers operated by RES across Canada– Full winter of data(October to May)– Anemometer height from 50 – 80m

Above 550 meters AMSL:

Sensors affected > 10% of time

Ho

urs

of

icin

g (

Oc

t-M

ay)

Mean hours of icing of unheated instrument vs Altitude

Cold Climate Measurement System

Cold climate measurement systems

Tubular 50-60m Lattice 80m

A2 A1

HE-V1HE-A1

A4

A5

A3

A6

V1

V2

- More expensive

+ Low maintenance cost

+ Re-use value

- Longer to install

+ Data @ Hub Height

+ Lower initial cost

- High maintenance cost

- Re-use value

- More likely to collapse

- No data @ Hub Height ?

Vaisala WAA252NRG IceFree

Cold Climate Met Mast Life Cycle

Assumption 1: 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

Cumulative Running Cost

Cos

t R

atio

Great Primary Mast

Met Masts Summary

• Good long term value

• Reduced shear uncertainty

• Potential for better data availability

80 m lattice

50 – 60 m tubular

• Good short term value

• Easier and faster to install Great Secondary Mast

Autonomous Power System

Small Wind Turbine RES Generators

1st generation

2nd generation

Wind Turbines 1 kW:

• Cheap: $10K• Max of 2 heated instruments• Not much flexibility • Eco-Friendly• Affected by trees• Tend to freeze

RES Generator:

• More: $35K• Many instruments• Flexible

• Close to 100% availability • Remote diagnostic tools • Easy to deploy

Heating system concept

RES Autonomous Power System Concept

Impact of CC on Project development

Tower InstallationTime constraints

Wind measurementIcing on InstrumentsLoad on met towers

MaintenanceSite accessCold Temp.

Development RFP Financing

Requirements

Predicted Wind

Predicted Energy

$/KWh Price

Predicted Wind

Predicted Energy

Higher Risks

Equity vs Debt

Winter 1 Winter 2 Winter 3

Pe

rce

nt

da

ta c

ap

ture

(%

)

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