Using satellite data for power flow estimation of an electrical low voltage grid with a high amount of photovoltaic systems

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1 3rd International Conference Energy & Meteorology (ICEM), Boulder, Colorado 26 th June 2015 Using satellite data for power flow estimation of an electrical low voltage grid with a high amount of photovoltaic systems

2 Outline Seite 2 Motivation General approach MSG irradiance data for transformer load flow Results Conclusion & Outlook

3 The electric grid A very short introduction Distribution Grid Transmission Grid Low Voltage Medium Voltage High Voltage >110kV Distribution Grid Today Grid operators have no measurements at the low voltage level P, B, U, I, kV Peak current readout every 1 to 4 years at transformer level 400V Seite 3 Photovoltaic (PV)

4 Seite 4 Distribution Grid Transmission Grid Low Voltage Medium Voltage High Voltage Meteorological data and the distribution grid asset Germany as a example >110kV Asset Absolute numbers Per km² Per MSG pixel MV lines 507,000 km 1.4 km/km² 21.3 km/px LV lines 1,160,000 km 3.2 km/km² 48.7 km/px HV/MV trafo 7, /km² 0.3 /px MV/LV trafo 560, /km² 23.5 /px PV systems 1,400, /km² 58.8 /px PV capacity 35,700 MWp 100 kwp/km² 1,499 kwp/px Per COSMO- DE pixel Per ECMWF pixel Germany = km², MSG pixel 15 km², COSMO-DE pixel 8 km² Sources: EWE Netz Gmbh and 20kV 11.1 km/px km/px 25.5 km/px km/px 0.2 /px 3.8 /px 12.3 /px /px 400V 30.7 /px /px 783 kwp/px 18,216 kwp/px

5 Voltage drop Influence of load and photovoltaic to voltage Voltage +10% (EN 50160) Nominal Voltage U -10% (EN 50160) Time Seite 5 Low voltage depends on Load depends on load profile Generation depends on irradiance Medium Voltage Level is a superposition of both

6 Seite 6 Test site 1 Suburban Ulm-Einsingen Situation 2013 Houses 133 PV Systems 21 Power 233 kwp Load: ~1047 MWh PV: ~ 230 MWh PV Fraction: 23%

7 Outline Seite 7 Motivation General approach MSG irradiance data for transformer load flow Results Conclusion & Outlook

8 PV system simulation Required data and available data Seite 8 Normally known by DSOs:

9 Seite 9 General approach Grid status with high shares of PV Roof potential analysis Shadowing Satellite images endorse-fp7.eu System data PV Modell Weather data Grid data Grid simulation Weather forecast Grid Status, Load flow, Voltage, Feed-in management Funded by EU-FP7, Project ENDORSE

10 Outline Seite 10 Motivation General approach MSG irradiance data for transformer load flow Results Conclusion & Outlook

11 Seite 11 Load flow calculation Approach M Irradiance PV nominal power PV Model j=1 Power over transformer Load = Generation PV Model parameters: Azimuth and tilt angles Ambient temperature Wind speed Irradiance on module N Annual Consumption Grid losses Load profile Real module and inverter characteristics Possible load profiles: Standard load profile Measured data SWU k=1 VDI 4655 Synthetic profiles Funded by EU-FP7, Project OrPHEuS

12 Satellite data for electric grids Satellite + Roof potential = Load flow Irradiance time series Real irradiance Transformer load flow GHI [W/m²] Seite 12 Clear Sky Own Calculations, Irradiance source: SOLEMI by DLR Funded by EU-FP7, Project OrPHEuS

13 Outline Seite 13 Motivation General approach MSG irradiance data for transformer load flow Results Conclusion & Outlook

14 Seite 14 Load flow at transformer Model Variation

15 Seite 15 Load flow at transformer Statistics of Average Day (Year 2012)

16 Seite 16 Load flow at transformer Annual load flow scatter (Year 2012) SOLEMI HelioClim 3 MACC-RAD Sun Ele < 0 Whole Day Sun Ele 15 Sun Ele 0

17 Seite 17 Load flow at transformer Relative Errors for SLP - Annual Results (Year 2012) Only values of sun elevation angles >0 are considered

18 Outline Seite 18 Motivation General approach MSG irradiance data for transformer load flow Results Conclusion & Outlook

19 Seite 19 Conclusion & Outlook Usefulness of satellite irradiance data in low voltage grids Overestimation of load flow Higher errors during morning and evening Load profiles as a source of error Reduction of relative errors compared with assumed demand-only load profile Next: Scaling up to medium voltage grid Replacement of meteorological ground measurement (temperature, wind speed) Combination with weather forecast technique The research leading to these results has received funding from the European Unions s Seventh Framework Programme (FP7/ ) under grant agreement No (project OrPHEuS), and from the German Federal Ministry of Education and Research support code 03FH030I3 (project NATHAN PV).

20 Thank you for your attention Any questions? Holger Ruf, Gerd Heilscher Hochschule Ulm - University of Applied Sciences Institut für Energie- und Antriebstechnik Eberhard Finckh Str Ulm Mail: ruf@hs-ulm.de heilscher@hs-ulm.de Florian Meier Stadtwerke Ulm/Neu-Ulm Netze GmbH Netz- und Anlagenplanung Karlstraße Ulm Tel.: 0731 / Mail: florian.meier@ulm-netze.de Marion Schroedter-Homscheidt Deutsches Zentrum für Luft- und Raumfahrt German Remote Sensing Data Center Oberpfaffenhofen Wessling marion.schroedter-homscheidt@dlr.de