Irradiance Forecasts for Electricity Production. Satellite-based Nowcasting for Solar Power Plants and Distribution Networks

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1 Chart 1 > European Space Solutions 2013 > 6th November 2013 Irradiance Forecasts for Electricity Production Satellite-based Nowcasting for Solar Power Plants and Distribution Networks Marion Schroedter-Homscheidt, DLR Gerd Heilscher, Holger Ruf, Hochschule Ulm Markus Hoyer, Flagsol GmbH

2 Chart 2 > European Space Solutions 2013 > 6th November 2013 Outline

3 Chart 3 > European Space Solutions 2013 > 6th November 2013 Distribution Network Example Stadtwerke Ulm

4 Chart 4 > European Space Solutions 2013 > 6th November 2013 PV Development Installed Power

5 Chart 5 > European Space Solutions 2013 > 6th November 2013 Grid Control Centre New Services???

6 Chart 6 > European Space Solutions 2013 > 6th November 2013 Service Concept roof potential shading satellite images PV system info PV model weather data grid data grid simulation weather forecast grid status, load flow, voltage, feed in management

7 Chart 7 > European Space Solutions 2013 > 6th November 2013 Smart Grid Test Sites Ulm Einsingen: (since 2011) Senden Hittistetten: (2013)

8 Chart 8 > European Space Solutions 2013 > 6th November 2013 Test Site Ulm Einsingen / Situation 2013 Households PV Systems Power 233 kwp Load: ~747 MWh PV: ~ 230 MWh PV Fraction: 31%

9 Chart 9 > European Space Solutions 2013 > 6th November 2013 Smart Grid Research Main Questions How much PV the grid can take? What happens when 25% / 50%.100% of the houses have PV systems? How the grid has to be enforced? Wich technical solutions are available? What are the costs? Which are the cost effective solutions? What are the costs for a Smart Grid?

10 Chart 10 > European Space Solutions 2013 > 6th November 2013

11 active power in kw irradiance in W/m² Chart 11 > European Space Solutions 2013 > 6th November 2013 Power Flow at the Transformer Sunny Day second-wise measurement

12 active power in kw irradiance in W/m² Chart 12 > European Space Solutions 2013 > 6th November 2013 Power Flow at the Transformer Partly Cloudy Day

13 Chart 13 > European Space Solutions 2013 > 6th November 2013 Dynamics Influence of the Medium Voltage Grid Dependency of load and generation Will get steeper with larger PV share or weaker grid dv Dependency on medium voltage active power change distribution of 60 seconds, phase U1

14 Cloud Type Chart 14 > European Space Solutions 2013 > 6th November 2013 Results (1/2) Example for Overcast Day Cloud Effects Optically thick

15 Chart 15 > European Space Solutions 2013 > 6th November 2013 Quantitative Parameters in a 49x49 Pixel Window , self similarity principle fractal dimension Koch s snow flake fractal dimension 1.26 source Wikipedia Global Irradiance

16 Chart 16 > European Space Solutions 2013 > 6th November 2013 Quantitative Parameters in a 49x49 Pixel Window Are parameters as fractal dimensions and/or number of clouds in an area good proxies for the occurence of fast changes ( ramps ) and bad predictability cases? Global Irradiance

17 Chart 17 > European Space Solutions 2013 > 6th November 2013 We can use cloud movements for nowcasting But let s have a look at another application first

18 Chart 18 > European Space Solutions 2013 > 6th November 2013 Solar Power Plant Production Forecasts In our case: Concentrating solar thermal technologies - with and without storage Large systems Example: Andasol-3 with base load capacity due to storage

19 Chart 19 > European Space Solutions 2013 > 6th November 2013 Use Cases in Grid Integration Transmission System operator (TSO) point of view grid stabilisation 15 minutes interval up to 1-2 hour forecast needed Power plant operator point of view (especially for CSP)

20 Chart 20 > European Space Solutions 2013 > 6th November 2013 Methods Applicable 48h deterministic forecast, 00 UTC run + ensemble forecast + statistical/mos approach Nowcasting cloud movement (IR, MSG) Nowcasting irradiance, cloud movement vectors aerosol monitoring

21 Chart 21 > European Space Solutions 2013 > 6th November 2013 It s a Non-Linear System solar field storage system power plant block

22 Chart 22 > European Space Solutions 2013 > 6th November 2013 Strategy to Use Nowcasting at the Power Plant Type A 48 h forecast made by weather service yesterday Type B Satellite images Now 45 Min Now 30 Min Now 15 Min now Human forecast with knowledge about upcoming cloud fields Type C Now 45 Min Satellite images Now 30 Min Now 15 Min now Automatic 8h-nowcast of upcoming cloud fields now Automatic 8h-nowcast of upcoming DNI values

23 Chart 23 > European Space Solutions 2013 > 6th November 2013 Thin ice and water clouds Medium and low direct normal irradiance source: Karlsruher Wolkenatlas

24 Chart 24 > European Space Solutions 2013 > 6th November 2013 low broken clouds high ice clouds low clouds Spectral channels allow discrimination of different clouds - an unique European opportunity stratiform clouds scattered cloud fields

25 Chart 25 > European Space Solutions 2013 > 6th November 2013 Example on Cirrus Clouds 3th May 2011, 0900 UTC Dust and cirrus special colors Dust pink, thin cirrus black

26 Chart 26 > European Space Solutions 2013 > 6th November 2013 Example on Dust Dust and cirrus special colors Dust pink, thin cirrus black

27 Bias DNI [W/m2] Bias DNI in W/m² Chart 27 > European Space Solutions 2013 > 6th November DNI forecast APOLLO cloud retrieval for MSG EUMETSAT/DLR EUMETSAT/DLR EUMETSAT/DLR EUMETSAT/DLR Cloud mask water clouds thin cirrus clouds 15 min update Receptor model cloud mask forecast Time lag in hours time lag in hours Validation example 10 UTC nowcast improves day ahead forecast (pink line)

28 Chart 28 > European Space Solutions 2013 > 6th November 2013 Power plant s operations control software Numerical Weather Prediction (incl. new MACC aerosol capabilities) Satellite imagery As visual help for the operator Satellite nowcasting Cloud movement Forecasting tool in operator s room DNI forecast Solar production forecast Reliable electricity market participation

29 Chart 29 > European Space Solutions 2013 > 6th November 2013 A Final Example

30 Chart 30 > European Space Solutions 2013 > 6th November 2013 Spatial structures of forecast errors? Dense ground measurements not available Satellite as option? ECMWF DNI forecast vs. SOLEMI (satellite obs) and BSRN observations Rel. RMSE, hourly day ahead 2006

31 FC-OBS FC-OBS Chart 31 > European Space Solutions 2013 > 6th November 2013 Spatial Error Correlations time time Corr coeff Correlation of errors -> larger grid areas are affected by the same programming error -> one should know as electricity grid operator direct normal irradiance Red = 2D-Gauss fitted ellipse Green = corr>0.5 ROI fitted ellipse

32 Chart 32 > European Space Solutions 2013 > 6th November 2013 Spatial Error Correlations global irradiance direct normal irradiance Red = 2D-Gauss fitted ellipse Green = corr>0.5 ROI fitted ellipse

33 Chart 33 > European Space Solutions 2013 > 6th November 2013 Structure of Spatial Error Characteristics Example: errors in France and Spain are not correlated good to know for grid direct normal irradiance planning thanks to satellite information global irradiance

34 Chart 34 > European Space Solutions 2013 > 6th November 2013 Summary Users requirement: We don t believe in an automatic system But please provide automatic and quantitative information Bibliographisches Institut, Mannheim We have shown relevance of information for solar electricity grid integration and ways how to use both satellite based imagery and quantitative derived information on irradiance conditions (amount, variability, nowcasting, forecasting, typical error structures ) Final goal of our work: saving money for hardware and in trading by using information

35 ENDORSE Pre-market downstream services in renewable energies Measures and observations Wind Sun Biomass Daylighting Load balancing C U S T O M E R S Develop products and services Help service providers to make use of GMES/MACC GMES/Land MSG Stimulate downstream sector in other countries -35

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