wind 101 – technical basics clean energy bc 2010 mark green – wind engineer, natural power...

Wind 101 – Technical Basics

Clean Energy BC 2010

Mark Green – Wind Engineer, Natural Power Consultants

• Practical consulting and risk management for the international renewable energy industry, providing services throughout the project life-cycle

• 15 year track record in wind energy consultancy - established in 1995

• Over 200 employees worldwide across 7 offices in 5 countries

• Consultancy services provided to more than 15,000MW of projects

• 2,000MW where we have provided full project design & consenting

• We have managed the construction of 500MW of wind energy

• 300MW+ of wind plant under our asset management

NATURAL POWER - ABOUT US

We have presence worldwide, including:

• Scotland (head office)• British Columbia, Canada• France• Ireland• England• Wales• Chile• USA

A GLOBAL PRESENCE

Our core services:

• Advanced resource assessment and site modelling

• Development, EIA and permitting

• Ecology services

• Construction and geotechnical services

• Site management

• Operational site analysis and optimisation

• 360o Due-diligence

OUR CORE SERVICES

1. Wind: The Basics

2. Commercial Background

3. Site Selection

4. Wind data collection

5. Data analysis – Long-term prediction

6. Wind flow modelling

7. Turbine layout and selection

8. Energy yield modelling

WIND 101 – OVERVIEW

The Basics

THE BASICS: WIND

• All renewable energy (except tidal and geothermal power) ultimately comes from the sun.

• Uneven heating of the earth’s surface causes differences in temperature throughout the atmosphere.

• Warm air, which weighs less than cold air, rises. Then cool air moves in and replaces the rising warm air.

• This movement of air is what makes the wind blow.

THE BASICS: TURBINES

Nacelle

Blades (35-55m length)

Rotor (70-110m diameter)

Rotor Hub

Tower (60-100m high) Transform

er

THE BASICS: WIND

•Maximum theoretical power in a moving fluid is defined in Watts…For wind, the power in the area swept by the turbine rotor:

P = 0.5 x rho x A x V3

•Betz law: maximum of 59% of the power moving through the rotor can be captured.

THE BASICS: WIND

• The Watt is the SI unit of power - instantaneous

• Energy in the context of electricity generation is the multiplication of power in Watts and time in hours.

• E.g. a 1MW turbine producing at 100% for 1 hour will produce 1MWh of energy.

• However, the wind never blows 100% of the time!

• The term Capacity Factor (C.F.) is used to describe the actual energy produced vs the max rated production.

What are the commercial drivers in performing technical analyses?:

• For a wind farm to receive financial backing, lenders and developers require a robust estimate of the lifetime energy yield (GWh)

• To secure wind turbines, a developer needs to demonstrate that the site conditions do not exceed the design and operational limits of the turbines

• The greater the uncertainty in the yield and design predictions, the greater the risk to the lender/developer

THE BASICS: COMMERCIAL BACKGROUND

• Desk-based resource modelling

• Short-term wind data collection

• Long-term wind climate prediction

• Wind flow modelling

• Energy yield modelling

• Uncertainty analysis

THE BASICS: PROCESS OF DESIGN & ANALYSIS

Site Selection

• Used for initial site prospecting

• Does not use any actual on-site wind data as an input

• Instead uses a local correction model

• Examples of regional mesoscale models are the Canadian Wind Atlas and the BC Wind Atlas, both are available online.

• Typically of too coarse a resolution and accuracy to be applicable in absolute wind resource assessment for financing

SITE SELECTION: DESK BASED MODELLING

SITE SELECTION: DESK BASED MODELLING

Economic Considerations:•Distance to transmission•Transmission capacity•Site access•Constructability •Wind speed

Technical constraints:•Forestry, topography, obstacles•Public rights of way, Parks•Microwaves/Telecommunication links, other Infrastructure (pipelines, etc.)•Ecology, Hydrology, Archaeology•Noise•Setbacks from other windfarms•Visual impact / Landscape / Shadow flicker

SITE SELECTION– CONSTRAINTS

SITE SELECTION– CONSTRAINTS

SITE SELECTION

Wind data collection

Why are on-site measurements required?

• Provide an accurate representation of the wind regime of the site and its viability

• Highlight localised wind flow issues

• Reducing prediction uncertainty

Measurement locations must be representative of turbine locations:• Topographically• Altitude• Exposure

WIND DATA COLLECTION

Duration and density of masts:

• Ideally, a “known point “ within 2km of every prediction location (depends on size and topography of wind farm)

• Particularly complex locations should be further investigated with additional monitoring/modelling

• 12 month minimum campaign


24


Cup anemometer

(measures wind speed)

Wind vane

(measures wind direction)

Prop Vane -

(measures wind speed and direction)


• Cylindrical mast:– For a mast with diameter, d, and

boom with diameter, D:• r/d > 8.5• R/D > 12

• Lattice mast– For a mast with face length, L,

and low porosity:• r/L > 5.7• R/D > 12

To achieve an industry best practice 0.5% deficit in wind speed or less:

R

r


• Masts – At least 2/3rds of hub height– Cup anemometers at 3 or 4 heights (for shear and turbulence profiles)– Collect 10 minute average speed, direction, SD, gusts, temperature,

pressure,

• Instruments– Vector, NRG, Thies, RM Young ... – Calibrated instruments (MEASNET wind tunnel)– Mounting adhering to best practice – Consider a mix of instruments


Remote sensing is another option:

• Ground based wind data collection

• LIDAR and SODAR

– Measure up to ~200m height

– Very useful for wind characteristics (shear, Ti) and for additional known points in complex flow

– Replacing masts in many applications

– LIDAR data is validated for project finance use



LASER

DETECTORTARGET

transmitted light

scattered and received light (with Doppler

frequency shift)

local oscillator (reference beam)

Wind Data Review

Perform quality checks on the data• Instrument continuity• Mast integrity (boom slippage)• Tower/instrument shadow• Shear profile• Turbulence• Icing affected data

WIND DATA REVIEW – REVIEW & PROCESSING

• Process and review the raw data recorded (Excel / Windographer / WAsP)

WIND DATA REVIEW – REVIEW & PROCESSING

• Site data collection will result in an onsite time series dataset of typically 1-2 years duration

• However, the wind farm annual energy yield prediction must be valid for the long-term mean annual average

– Wind farm life is 20-25 years

• We must therefore adjust the short-term site data to make it representative of the long-term mean annual wind climate

WIND DATA REVIEW – LONG TERM PREDICTION

Main tool to achieve the long term correlation is MCP:• MEASURE wind speed and direction at the wind farm site• CORRELATE between the wind farm site data and wind data from a suitable long-

term reference weather station (Environment Canada station)• PREDICT the long-term wind climate at the site

The keys to MCP are:• Establishing good correlations• Consistency of measurement

WIND DATA REVIEW – LONG TERM PREDICTION

WIND DATA REVIEW – REFERENCE STATIONS

Wind flow modelling

• The data analysis and MCP process results in a prediction of the long-term mean annual wind climate (frequency of speed and direction)

• This data is valid only at the height and location of the principal site anemometer (s) dataset used in the analysis

• The turbines in the wind farm will be situated across the project area

• The wind climate will vary across the site with changes in exposure, topography, surface roughness

• The wind climate must therefore be extrapolated horizontally and vertically to the hub-height of all turbines within in the wind farm

WIND FLOW MODELLING

• WAsP/Ms-Micro flow model– Simple, quick, easy to run– Assume flow is always attached (i.e. no turbulence)– This severely limits their use in complex flow environments (steep

slopes/forests) – can lead to significant model errors

• Simple flow models are being replaced by advanced 3D computational fluid dynamics (CFD) models (such as Ventos)

– Designed to deal specifically with complex terrain and forestry– Complex, computationally demanding, require expert use– Applicable also in determining areas of flow disturbance – the wind

quality – for turbine micro-siting

WIND FLOW MODELLING

What causes complex flow?• Forestry• Terrain• Obstacles

Complex flow impacts wind flow quality

Flow parameters that define the wind quality :• Wind shear• Turbulence• In-flow angle

WIND FLOW MODELLING: COMPLEX FLOW

WIND FLOW MODELLING: COMPLEX FLOW

Shear : Variation of horizontal wind speed with height

Characterised by log or power law profile

Effects : Increased fatigue loadingReduced power output

Values : Power law exponent ≤ 0.3

WIND FLOW MODELLING: SHEAR

Turbulence : The formation of eddies and vortices (transient)Characterised by turbulence intensity (TI%)

Effects : Reduced power outputIncreased fatigue loading

Values : IEC limit ≈ 12 – 16 % @15m/s (Class A/B/C)

WIND FLOW MODELLING: TURBULENCE

Inflow Angle : Deviation of the directional component of the wind velocity from the turbine rotor axis in the vertical plane.

Effects: Reduced power outputIncreased fatigue loading

Values: θ ≤ 8° (±)

θ

WIND FLOW MODELLING: INFLOW ANGLE

WIND FLOW MODELLING: TURBULENCE

WIND FLOW MODELLING: RECIRCULATION

Forestry felling or management options• Scenario modelling with Ventos CFD flow model• Potential improvements in wind quality and resource

Sector-wise curtailment• Preserve turbine integrity• Maximise availability/energy in “clean” sectors

Maintenance and repair strategy• Target maintenance and repair by turbine and component

WIND FLOW MODELLING: MITIGATION

TURBINE LAYOUT AND SELECTION

Wind farm should be designed to meet physical and technical constraints whilst utilising the maximum potential from the wind

Other optimisation criteria:• Inter-turbine spacing (4-8 rotor diameters / circular or elliptical). Much greater

offshore• Hub height• Proximity to trees (> 50 x tree height) – optimal not always practical• Proximity to noise sensitive properties - allowable noise limit in BC - 40dBA at

night• Maximise energy output

TURBINE SELECTION AND LAYOUT DESIGN

Wind turbines are certified for different site conditions according to international standards (IEC/GL/DNV)

Principle criteria are:• Average wind speed• Maximum 50-year return 3 second gust• Ambient site turbulence• Vertical wind shear and inflow angle• Temperature ranges

Suitable turbine selection is necessary for warranty and economic optimisation

TURBINE SELECTION: CLASSIFICATION

Sites defined as either:– Class I: Most severe site wind climate– Class II: Moderate site wind climate– Class III: Least severe site climate

– Sub-category for ambient site turbulence at 15m/s (A/B/C)

TURBINE SELECTION: CLASSIFICATION

Energy Yield Modelling, Losses & Uncertainty

The basic principles…..• Take the “instantaneous” turbine power curve (power in kW)• Combine with a wind speed frequency data for the location (time in hrs)• Calculate the generated electricity yield (energy in kWh) for the time period• Apply losses

Power (kW)

x Time (hours)

= Annual Energy (kWh)

ENERGY YIELD MODELLING

Typically performed in wind farm design software• WAsP/WindFarmer/WindFarm/WindPro/OpenWind

Output is an “ideal” mean annual energy yield value for each turbine

Losses to apply• Production losses• Array losses due to turbine wake interaction

ENERGY YIELD MODELLING

• Losses are applied for a range of energy production issues:

– Turbine availability (~3-5%) - Estimated or based on warranty

– Grid availability (<1%) - Estimated

– Electrical losses (~1-4%) – Calculated to metering point

– Blade performance (<1%) – Estimated – site dependant• Icing, degradation

– Control losses (~1%) – Estimated/calculated - site/turbine dependant

– Curtailment losses (grid restriction, noise, shadow) – site dependant

ENERGY YIELD MODELLING: LOSSES

Array Losses:

• Often most significant loss in a large wind farm arrays

• Wind turbines create a disturbance downwind as kinetic energy in the wind is converted to mechanical energy by the rotor – the “wake”

• In the turbine wake, wind velocity generally decreases and turbulence increases.


All stages of the modelling process have uncertainties associated with them:

– Data collection

– Long-term correlation

– Wind flow modelling

– Wake modelling

– Loss prediction

We must also account for the natural variability of wind over different time-periods

ENERGY YIELD MODELLING: UNCERTAINTY

How to reduce uncertainty:

• Give a high priority to quality on-site data collection and checking

• Collect as long a data-set as possible

• High density data collection – numerous points and heights

• Use an appropriate flow model for the site

• Reference data – careful selection of station and reference period to ensure consistency, veracity and applicability


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The End. Thanks!

wind 101 – technical basics clean energy bc 2010 mark green – wind engineer, natural power...

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