current status of solar pv power forecasting · current status of solar pv power forecasting elke...

19.11.2013, MeteoRES workshop, Oldenburg, Germany 11

Current status of solar PV Power forecasting

Elke Lorenz Jan Kühnert, Annette Hammer, Detlev Heinemann

AG EnergiemeteorologieUniversität Oldenburg


Outline!background: forecast requirements for trading of PV power

!overview on operational PV power prediction system*

!irradiance forecasting: combination of satellite and NWP forecasts

!PV power forecasting: evaluation for control area of transmission system operator 50Hertz

!summary and outlook

* cooperation with Meteocontrol GmbH

19.11.2013, MeteoRES workshop, Oldenburg, Germany

Contribution of PV systems to electricity supply in Germany !installed PV power (end 2012): 32 GWpeak in Germany

!up to 42% of electricity demand from PV

!strong variability of solar and wind power

22 GW


Balancing of solar power according to renewable energy sources act !mandatory purchase of all available renewable electricity by grid operators

!marketing and balancing of PV power by transmission system operators (TSOs) based on their respective share of the all German electricity supply (horizontal burden sharing)

!additional option of direct marketing of PV power is getting more important

need for regional forecasts

control areas of transmission system

operators


Balancing of solar power input (RES act)by transmission system operators

!day-ahead: selling of PV power at the European Power Exchange (EPEX)

!hourly contingents !12:00 for the next day

-

hourly forecasta for next day



!day-ahead: selling of PV power at the European Power Exchange(EPEX)


!intra-day: trading of electricity at the EPEX

!hours or 15-minute periods!until 45 minutes before deliveryforecast errors influence prices

-

15min resolution forecast for next hours



!day-ahead: selling of PV power at the European Power Exchange(EPEX)


!intra-day: trading of electricity at the EPEX

!hours or 15-minute periods!until 45 minutes before deliveryforecast errors influence prices

!remaining deviations are adjusted with balancing power

-

forecasts with15 min resolution for the next hours

-

online-estimation from measured values


DWD forecast

ECWMF forecast

representativePV system sites

power predictionPV simulation

up-scaling

optimized, site-specific irradiance

prediction

regional PV power prediction

Satellite data

irradiancemeasurement

20

module typenominal powerTilt and orientation..

PV system description

PV powermeasurement

irradiance forecastingforecasthorizon

hours

days


Meteosat Second Generation (high resolution visible range)

!cloud index from Meteosat images with Heliosat method

resolution in Germany!1.2km x 2.2 km !15 minutes

Irradiance prediction based on satellite data



!cloud motion vectors by identification of matching areas in consecutive images

!extrapolation of cloud motion to predict future cloud index


Meteosat Second Generation (high resolution visible range)


satellite derived irradiance maps


!cloud motion vectors by identification of matching areas in consecutive images

!extrapolation of cloud motion to predict future cloud index

!irradiance from predicted cloud index images with Heliosat method


200W/m2 900W/m2


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Evaluation of irradiance forecasts: data sets! period: 1.1.-30.9.2012

! measurements:irradiance measurements of 270 stations in Germany, operated byDWD and meteomedia GmbH

! forecasts:! DWD ! ECMWF! CMV! Combined forecasts


Evaluation: combination of ECMWF, DWD and CMV forecasts

date

I in

W/m

2

CMV: Cloud Motion Vectors


Evaluation: combination of ECMWF, DWD and CMV forecasts

date

I in

W/m

2


Evaluation: 3 hour ahead forecastscombination of ECMWF, DWD and CMV

for 3 hours ahead satellite based forecasts in average significantlybetter than NWP forecasts, but outliers may occur

mean Germany

rmseECMWF 41W/m2

rmseCMV 34W/m2

CMV,



combination much better than single models ccerror(ECWMF,DWD)=0.51, ccerror(ECWMF,MVF)=0.29

mean Germany

rmseECMWF 41W/m2

rmsecmv 34W/m2

rmsecombi 25W/m2

improvement*

vs ECMWF39%

improvement*

vs MVF26%

CMV,

*



combination much better than single models: in particular outliers are reduced

mean Germany,rmse Δmax

ECMWF 41W/m2 167W/m2

CMV 34W/m2 -177W/m2

combi 25W/m2 113W/m2

cmv

19.11.2013, meteoRES workshop, Oldenburg, Germany

Evaluation: rmse in dependence of forecast horizon

!CMV forecasts better than NWP based forecast up to 4 hours ahead

!CMV forecast better than persistence of cloud situation from 2 hours onwards

!large improvement with combined model

calculation time of MVF: sunel > 10°only hours with all models available included in dependence on forecast horizon

19.11.2013, meteoRES workshop, Oldenburg, Germany

Evaluation: rmse in dependence of forecast horizon

improvement with combined forecasts more pronounced for regional average forecasts


Evaluation of day-ahead irradiance forecasts combination of ECMWF and DWD

mean Germany

rmseECMWF 43W/m2

rmseDWD 51W/m2

!ECMWF irradiance forecasts better than DWD irradiance forecasts


Evaluation of day-ahead irradiance forecasts combination of ECMWF and DWD

mean Germany

single sites

rmseECMWF 43W/m2 107W/m2

rmseDWD 51W/m2 114W/m2

rmsecombi 40W/m2 103W/m2

improvement 8% 4%

!ECMWF irradiance forecasts better than DWD irradiance forecasts

! improvement with combined approach


DWD forecast

ECWMF forecast

representativePV system sites

power predictionPV simulation

up-scaling

optimized, site-specific irradiance

prediction

regional PV power prediction

Satellite data

irradiancemeasurement

38

module typenominal powerTilt and orientation..

PV system description

PV powermeasurement

forecasthorizon

hours

days

PV power prediction

*Cooperation with Meteocontrol GmbH


Data sets!control area 50Hertz

!December 2011- November 2012

!hourly values

!PV measurements:

!monitoring data Meteocontrol: > 1000 PV systems, ca. 20% of installed power

!single site evaluation: 80 selected systems

!measurement of overall PV power feed-in control area not available

41

Sel


Estimation of PV power feed-in in control area

!Upscaling using Meteocontrol monitoring data

!all systems in the control area

!considering spatial distribution with 2digits PLZ resolution*

!considering distribution of PV system size*

!overall installed power Pnom (given by 50Hertz)

42

*based on „EEG Data“ 16.8.2012


43

Data sets!forecasts

!06:00, 1-3days ahead

!11/11-05/12: ECWMF only

!06/12-11/12: ECMWF & DWD

!11:00, intra-day

!09/12-11/12: combination of NWP and CMV


Evaluation

only daylight values,normalization to installed power

control areacontrol area single sitessingle sites

bias* rmse* bias* rmse*

Intra-day

0.9% 4.9% 1.1% 12.0%

day-ahead

0.7% 5.7% 1.2% 12.8%

3days 0.5% 6.2% 0.9% 13.4%


Evaluation:annual course of forecast errors

!largest rmse values Feb-April 2012


!largest rmse values Feb 2012 snow



!largest rmse values Feb-April 2012 snow and fog


50Hertz, day-ahead, April 2012


!largest rmse values Feb-April 2012 snow and fog

!from June onwards: combination of DWD and ECMWF irradiance forecasts



EvaluationEvaluation:timeseries


Evaluation:combination NWP and satellite based CMV forecasts

o NWP, 06:00x combi, 11:00

o NWP, 06:00x combi, 11:00

large improvement with combined model


54

Summary !PV power prediction contributes to successful grid integration of more than 32 GWpeak PV power in Germany

!irradiance forecasts based on satellite data significantly better than NWP based forecasts up to 4 hours ahead

!significant improvement by combining different data sources, in particular when combining satellite and NWP based forecasts

!need for further research (in particular for fog and snow)


55

Outlook

!integration of additional data sources:!different NWP systems!additional meteorological parameters!cloud detection with IR satellite images!online measured PV power data

!advanced statistical methods to integrate the different data sources

current status of solar pv power forecasting · current status of solar pv power forecasting elke...

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