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  • Country scale solar irradiance forecasting for

    PV power trading

    The benefits of the nighttime satellite-based forecast

    Sylvain Cros, Laurent Huet, Etienne Buessler, Mathieu Turpin

    7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    European power exchange (EPEX)

    ■ Power organised SPOT market

    – Day-Ahead auctions:

    • Electricity traded for delivery the following day at 24-hour time step

    • The daily auction takes place at 12:00 pm, 7 days a week

    – Intra-day trading:

    • Electricity traded for delivery on the same or the following day at 15 min

    time step

    • Trading is continuous 7 days a week and 24 hours a day (up to 30 min.

    before physical delivery

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Intraday trading

    ■ Solar energy is a variable source of electricity

    ■ Intraday power trading leads to fill the gaps at the best price

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Unbalances adjustements

    ■ PV power forecast helps to :

    • Optimize trading prices

    • Avoid costly adjustment

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Intraday forecast for EPEX market: a

    German use-case ■ Every morning at 6 am CET, the customer wants:

    – Forecast of total Germany PV power production eligible to EPEX

    – 15 min time step until 12am CET

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    German PV production 2016-08-07 (MW)

    Actual production

    PV capacity map

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    How to get an intraday country

    scale PV power forecast?

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    German PV production 2016-08-07 (MW)

    Actual production

    NWP

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    How to get an intraday country

    scale PV power forecast?

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    German PV production 2016-08-07 (MW)

    Actual production

    NWP

    Satellite

    Forecast delivery time

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    How to get an intraday country

    scale PV power forecast?

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    German PV production 2016-08-07 (MW)

    Actual production

    NWP

    Satellite

    Night Satellite

    Forecast delivery time

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    How to get an intraday country

    scale PV power forecast?

    ■ Objective: quantifiying the benefit of night satellite-based forecast for

    trading applications

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    German PV production 2016-08-07 (MW)

    Actual production

    NWP

    Satellite

    Night Satellite

    Machine-learning combination

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Country forecast using satellite data

    ■ Extrapolation of cloud index pattern (Cros et al., 2014) from

    Meteosat-10 satellite

    Cloud motion vector field on T0 HRV map Forecasted Cloud index maps – Up to 6 hours (step 15 min)

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Forecasting before the sunrise

    ■ If the sun is below the horizon :

    No cloud data available with VIS channel: => forecast is not possible

    ■ Delivering forecast at 6:00 CET only possible few days in summer

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    ■ Using Meteosat-10 IR channels (10.8 and 3.6 µm) to synthetize a

    « Heliosat compatible cloud index » before the sunrise

    A night cloud index

    2016-05-26 00:00 to 10:00 UTC

    ■ Approach of Hammer et al. (2015):

    – Cloud maintain their distinctive features during few hours between night and day time

    – Statistical relationships between HRV cloud index and brightness temperature related value are established

    Cloud index 2016-05-26 00:00 to 10:00 UTC

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    A night cloud index

    ■ Statistical relationships between HRV channel cloud index and

    brightness temperature related value are established

    ■ Obtaining cloud index - not only a cloud mask - without NWP

    profiles

    From Hammer et al. (2015)

    Fog and stratus Very cold clouds

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    HRV reflectance correction

    ■ Our modifications for night-day transition

    85° < SZA < 89.8°

    X = 1/(cos θ + 0.025*exp(-11* cos θ)) When 85 < θ < 89.8° Rozenberg (1966)

    θ: solar zenithal angle

    ■ Cloud index is overestimate when the sun is low

    ■ An airmass correction is needed for pixel reflectance

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    HRV reflectance correction

    Airmass correction from Hammer et al., (2015)

    Cloud index 2016-07-16 4:15 UTC Cloud index 2016-07-16 4:15 UTC

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    HRV reflectance correction

    Cloud index 2016-07-16 4:15 UTC Cloud index 2016-07-16 4:15 UTC

    New airmass correction more appropriate for reflectance computed from calibrated radiance on Heliosat-2 (Rigollier et al., 2004) based method

    ᑭ’ = ln (1+ ᑭ/a)*a

    a = 15/(|θ-75|+000.1 ) * 2

    Empirically decreasing highest reflectance values

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Irradiance night satellite forecast

    assessment ■ Full year 2016 over 23 DWD stations (hourly irradiation, free access)

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Satellite-based forecast assessment

    ■ Night: θ > 89.8° ; Day θ < 89.8°

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    1 2 3 4 5 6

    Relative RMSE (%)

    All

    Night

    Day

    Time horizon (h)

    R el

    at iv

    e R

    M SE

    ( %

    )

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Satellite-based forecast assessment

    ■ Night: θ > 89.8° ; Day: θ < 89.8°

    Night

    All

    Day

    Time horizon: 3h

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

    Country forecast – Statistical approach

    Random forest

    Algorithm

    Historical PV production

    Measurements (EPEX SPOT archives)

    Training Country power

    forecasts

    NWP

    (ECMWF, ICON, GFS)

    Satellite

    (Hourcast – Reuniwatt)

    Night Satellite

    (Hourcast – Reuniwatt)

    PV power capacity

    map

    Seasonnality

  • 7th Solar Integration Workshop on integration of Solar Power into Power Systems | 24-25 October, Berlin, Germany

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    NWP

    Night Satellite

    Machine-learning combination

    Country Forecasting –

    Statistical Approach ■ Typical successful case: night satellite forecast « warns » NWP that

    Germany is more cloudy than expected this early morning

    ■ Random forest algorithm behaves according to its training and to

    the symmetry of the daily production profile