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Nowcasting CNN

Model description

3d conv model, that takes in different data streams

    architecture is roughly
    1. satellite image time series goes into many 3d convolution layers.
    2. nwp time series goes into many 3d convolution layers.
    3. Final convolutional layer goes to full connected layer. This is joined by
    other data inputs like
    - pv yield
    - time variables
    Then there ~4 fully connected layers which end up forecasting the
    pv yield / gsp into the future

Intended uses & limitations

Forecasting short term PV power for different regions and nationally in the UK

How to use

[More information needed]

Limitations and bias

[More information needed]

Training data

Training data is EUMETSAT RSS imagery over the UK, on-the-ground PV data, and NWP predictions.

Training procedure

[More information needed]

Evaluation results

[More information needed]

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