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AIP-2 Kickoff Workshop Energy SBA Scenario Answer Thierry Ranchin, Mines ParisTech, France Team: Mines ParisTech, DLR, JRC, NASA MeteoTest, Rutherford.

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Presentation on theme: "AIP-2 Kickoff Workshop Energy SBA Scenario Answer Thierry Ranchin, Mines ParisTech, France Team: Mines ParisTech, DLR, JRC, NASA MeteoTest, Rutherford."— Presentation transcript:

1 AIP-2 Kickoff Workshop Energy SBA Scenario Answer Thierry Ranchin, Mines ParisTech, France Team: Mines ParisTech, DLR, JRC, NASA MeteoTest, Rutherford Appleton Lab GEOSS AIP-2 Kickoff September 2008

2 Scenario objectives Support the SBA Energy by developing services providing irradiance data among other parameters Simulating the case of the sitting of a solar power plant.

3 ?

4 From the users point of view StepDescription Step 0The investor asks a consulting company for a study for a given geographical area Step 1The consulting company wants to obtain the necessary information and puts requests to the GEOSS portal Step 2The specific application is invoked Step 3The specific application invokes various web services and resources to retrieve needed information. It then invokes the specific processing web services. Step 4The specific application packs the layers as an archive file and deliver it to the consulting company Step 5The consulting company retrieves the archive, performs the study by exploiting the retrieved information and its own models and reports to the investor Step 6The investor takes a decision Request Answer Process

5 2. Meteorological, geographic and tools already available

6 Meteorological data Access through WSDL to databases: –Monthly means of solar irradiance –Min, max and mean values of air temperature at 2 m –Min, max and mean values of relative humidity at 2 m –HelioClim 3 time series of irradiance (year 2005) –Forecast of meteo data at surface for 3 days to 3 hours –SOLEMI time series irradiance data –NASA–SSE–HelioClim 1 times series of daily irradiance Other types of access –Real time information meteorological data Providers: Mines ParisTech, NCAR, DLR, NASA, Rutherford Appleton Lab

7 Geographical information SRTM Data worldwide 3 arcsec (~90 m) Shaded area derived from SRTM Local maximum slope

8 Tools PV assessments through PVGIS Server (JRC) Stochastical generation of test datasets for modelling of PV system (MeteoTest) PV Production calculator (MeteoTest) Computation of renewable energy parameters (NASA)

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10 Geographical data Source from SRTM DEM, results from specific processing. 100 meters resolution Ratio between actual daylength with shadows and astronomical daylength (%) Altitude in meters Local maximum slope in degree

11 Geographical data: Hydrology and usage Security cooling device for Solar Plants –Need an important flow of cooling water (typically 2 m 3 /s for a 12 MW Solar Plants) –Estimated cost for the linking to the Hydraulic Network Maps depends on the linking length (typically 300 k/km) –Need Hydraulic Network Maps (Map scale better than 1/ ) Hydraulic network. Scale 1/ Sample of estimated cost of hydro network linking in Keuros

12 Geographical data: Electricity network and usage Linking to High Voltage Electric Network –Estimated cost for the linking to the HV Electric Network Maps depends on the linking length (typically 200 k/km) –Need High Voltage Electric Network Maps (Map scale better than 1/ ) Estimated cost of electric network linking KeurosElectric network. Scale 1/

13 Environmental data Protected area & risk and hazard –Cope with regulation –Adequacy between the solar plant lifecycle and ROI Protected area. Scale 1/ Risk and Hazard. Scale 1/

14 Input parameters & output result Inputs: –bounding box (lat., lon.), dates, scale, optional layers, valid address Output results: –the geo-referenced layers (GeoTIFF, shape files) should be provided as a downloadable archive


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