Project Overview

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Second International Seminar on Technologies for
Electricity Production Based on Sea Waves and
Tidal Currents
M4 WAVE ENERGY RESOURCE
CHARACTERIZATION Teresa Pontes
Antonio Falcão INETI /
LNEG IST Lisboa, Portugal
Universidad Catolica de Chile , Santiago
15-16 November 2007
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OUTLINE

• Sea state description
• Data Sources
• Measurements (in situ and remote sensed)
• Numerical Wind-Wave Models
• Wave Resource Statistics
• Atlases and Databases

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Sea State Description

• Linear theory H wave height
  ? - wave length
• Sea states are described in frequency and
  direction ? by
• Directional Spectrum
• Energy or frequency
  spectrum
• Spectral moments
• are used to compute H, T, ? parameters that
  summarize sea states

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Sea State Description - Most Used Parameters
Hs significant wave height
Te energy (mean) period
Tp peak period
?m mean direction
P power (energy flux /unit crest length)
Cg energy propagation (group) velocity

Deep water (hgt?/2)
P ? 0.5 Hs2 Te
h water depth
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E(?) ?(?)
Spectral analysis
Sea surface easurements
swell
wind sea
S(?,?)
Wave Power parameters Hs, Te, Tp, P, ?
Long-term statistics
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Data Sources

• Measurements
• Visual observations
• In situ buoys, pressure probes, acoustic
  sensors, ADCP (Doppler),..
• Remote Sensed satelite (altimeter, SAR),
  ground-based radar
• Numerical Models

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Wave Data Sources and Types
satelite
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Visual Observations

• First source of wave data, on board of
  commercial ships
• Being compiled since 1850s from British ships
• Accuracy
• Direction - Good
• Wave height - Acceptable
• Period - Lower quality
• Long term data sets
• More useful to identify whether
  short-to-medium-term accurate data can be
  considered representative of long term
  conditions.

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In situ Measurements

• Ground truth. The most realistic data.
• Not widely available - expensive and difficult
  due to harsh environment
• Measuring systems wide range of techniques and
  deployment
• Moored buoys
• Fixed structures
• - Laser and acoustic sensors - Suspended over
  sea surface -
• - Wave staff - penetrates the water surface
• Bottom-mounted pressure and acoustic sensors
• Selection
• depends on depth, access, wave conditions, data
  details (directionality).

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Moored Buoys
Wavec Buoy
Directional Waverider Buoy
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Remote Sensed Measurements

• Satellite Radar Altimeter
• Satellite Synthetic Aperture Radar (SAR) not
  useful for wave energy
• Ground-based radar
• Advantages
• No failures due to bad weather
• Disadvantages of satellite-based systems
• Low frequency of measurements ERP - Exact
  Repeat Period - 10 to 35 days
• Distance between tracks 0,8º to 2,8º along
  Equator

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Topex Altimeter
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Radar Altimeter

• Measures sea surface elevation
• Hs
• U10 - (wind velocity at 10m height)
• Hs - Accuracy similar to buoy data
• Models developed to compute wave period T from
  altimeter data
• Three satellite altimeters are currently in
  operation
• Availability in Near Real Time (NRT) 4 h

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Satellite Altimeters
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Topex-Poseidon tracks
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Topex Altimeter / Buoy Verification

Portugal North West Coast

• 3 Datawell Buoys data - FF, L1, L2
• E(?) 3-hour h ? 90 m
• 1991-1992 40 pairs buoy Topex
• Collocation distance max 30km
• Collocation max time 1h

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Altimeter Buoy Verification - Hs

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Altimeter Buoy Verification Te
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Altimeter Buoy Verification P (lt 100 kW/m)
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WAVE ENERGY RESOURCE - SOUTH AMERICA INETI 2006
TOPEX Hs data, Te computed using Davies et al.
(1998) model
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SPATIAL VARIABILITY
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Numerical Wind-Wave Models

• Solve energy density balance equation at the
  nodes of a grid covering the ocean (at global,
  regional or local scale)
• Input wind fields over the ocean produced by
  an atmospheric model

S sum of energy source sink terms

• Accuracy presently very good
• Operation
• Forecast mode (from predicted wind fields) 10
  / 5 days
• Hindcast mode (from past wind fields)
• e.g ECMWF, ERA-40 global hindcast available
  for 1957-2002

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Main Global Wind-Wave Models
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Forecasts of Wind-Wave Model MAR3G Portugal
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Complementarities of Wave Data

• Measured data and model results are complementary
  
• They are jointly used
• e.g.
• TOPEX altimeter Hs - used for model results
  verification (WERATLAS)
• WAM model results used to initiate the
  computation of the ENVISAT satellite SAR -
  directional spectrum
• GLOBwave project 2007 - facilitate sharing of
  wave data
• Coordinated by IFREMER (France) European Space
  Agency (ESA)

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MAIN ATLASES AND DATABASES (I)

• Global Wave Statistics (1986)
• Book based on visual observations
• WERATLAS - European Wave Energy Resource Atlas
  (1996)
• EU Electronic offshore atlas Atlantic and
  Mediterranean coasts of Europe
• Based on ECMWF WAM model results verification
  against buoy and TOPEX data
• World Wave Atlas (1996)
• Altimeter GEOSAT (1986-89) Topex (1992-97) Hs
  and U10 data

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MAIN ATLASES AND DATABASES (II)

• ONDATLAS (2003)
• Portugal nearshore wave energy resource atlas
• Atlas of UK Marine Renewable Energy Resources
  (2004)
• Specifies and maps potential wave, tidal and
  offshore wind resource
• Accessible Wave Energy Resource Atlas Ireland
  (2005)
• Maps theoretical, technical and accessible
  resource
• WORLDWAVES (2005)
• Package containing offshore database (with
  bathymetric data), shallow water models,
  statistical wave analyses packages

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Statistics
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Annual Relative Frequency (Hs, Te) (all
directions)
Maximum frequency of occurrence -
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Portugal - Annual P distribution against Hs and
Te

Maximum P contribution -
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Lisboa WERATLAS - Monthly Variability of Hs

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Lisboa WERATLAS - Monthly Variability of P
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Thank you for your attention