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Wind Energy Community of Practice Dr. Thierry Ranchin, Ecole des Mines de Paris Mark Ahlstrom, WindLogics/IEEE Dr. Charlotte Bay Hasager, Risø (and other.

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Presentation on theme: "Wind Energy Community of Practice Dr. Thierry Ranchin, Ecole des Mines de Paris Mark Ahlstrom, WindLogics/IEEE Dr. Charlotte Bay Hasager, Risø (and other."— Presentation transcript:

1 Wind Energy Community of Practice Dr. Thierry Ranchin, Ecole des Mines de Paris Mark Ahlstrom, WindLogics/IEEE Dr. Charlotte Bay Hasager, Risø (and other proposed CP members)

2 Objectives – Wind Energy CP Support GEOSS outcomes related to application of EO data toward valuable wind energy results: –Siting –Design –Forecasting –Integration –Operation Wind energy community: users of the energy, suppliers of systems and components, electricity transmission and distributions operators, providers of services, market players

3 Societal Benefit Why Wind Energy Now? Mature technology Wind is fastest growing source of energy in the world today Huge potential in both developed and developing countries Dramatic benefit in improved siting, energy varies with cube of wind speed Improved forecasting crucial to utility integration and operations

4 Justification Requires interdisciplinary knowledge and disparate information that go beyond existing collaborative activities: –Weather data archives for site modeling –Weather forecasting in all timeframes –Boundary layer meteorology –Climate analysis and long-term variability –Extreme event analysis and temporal change –Turbulence information –GIS, land use data, surface roughness data, orography –Ocean parameters –Infrastructure compatibility –Environmental impacts

5 Earth Observation for Wind AdvantagesLimitations Wide area observations (e.g. met mast gives only point data, can there be a better site nearby?) Ability to monitor remote places in a non-intrusive & objective manner Uniform in space, consistent in time, cost-effective Ability to go back in time (e.g. existence of archive to detect changes, trend). Ideal for decisions regarding long-term investment such as wind farms. Indirect measure - need ground truth (i.e. less accurate than in- situ) Limited sampling (space, time, holes, clouds) Availability (e.g. SAR?) Need value-adding to turn data into information

6 Offshore Wind Energy Active remote sensing for resource assessment Scatterometer Coarse Resolution (O(25)km) Good temporal frequency Long-term archive BUT does not work close to coast where wind farms are built Synthetic Aperture Radar High Resolution (O(150)m) BUT Low temporal revisit Archive (mainly ERS, ENVISAT, RADARSAT) Need to combine EO sources BUT better used to get the spatial variability rather than magnitude Courtesy RISOE (DK)

7 Offshore Wind Energy EO-based wave statistics to support design of vessels for operations & maintenance and fatigue loading estimation EO-based water quality data for Environmental Impact Assessment MERIS data Courtesy ESA Courtesy ARGOSS (NL) & BMT (UK) What is the availability of wind farms? Can I send a vessel to repair? What kind of vessels? Should I invest in maintenance or more turbines?

8 Onshore Wind Energy EO-based roughness & Digital Elevation Model for wind modelling Contributing to Enhanced Wind Energy Modeling Results Courtesy ARMINES (FR)Courtesy WindLogics (USA)

9 Raw EO data Information & ServicesEnd-User Application Backscatter from Synthetic Aperture Radar Wind rose retrieved through numerical model of boundary layer Integration with ancillary data Sources into user software Adding to the Value Chain Aim to make the end-to-end EO value chain more effective by: Delivering information services Organising the supply (e.g. developing infrastructure and standards) Federating the demand (e.g. user-pull, not technology pushed)

10 Wind Life Cycle / Data Needs Courtesy Armines (Fr) Services Resource Assessment: Nowcast - NRT monitoring Hindcast - archive Forecast - modelling Services Environmental Impact Data Issues: Error bar (DA, risk) Certification Benchmark Data Requirements depend on the phase

11 Wind energy can be the model for a broader Renewable Energy Community for GEOSS Innovation Algorithms Feedback Applications ServicesScience

12 Structure of WE CP Steering Committee with worldwide representation –End users –Experts –Participants from the national or international programs –Participants from space agencies –Policy makers/analysts Core Working Groups –Experts –Members of the Community of Practices

13 Activities Development of core working groups Workshops for users Standardisation (Metadata, protocols, architecture, databases, information…) Building networks and develop incubation projects Coordination of users requirements across energy societal area and societal benefits areas Favouring business development Disseminating and educating GEOSS potential and best practices

14 Products and Schedule for Approval of TOR and CP (Dec 2005) Initiate user survey (Feb 2006) Workshops (TBD in 2006, 2007) Draft report and recommendations (July 2006) Report to User Interface Committee (Nov 2006) Initiate Incubation projects through virtual centers (early 2007) Coordinate developing of networks of Databases and Information (2007) Outreach activities ( )

15 Wind Energy Community of Practice Courtesy WindLogics (USA)


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