Try CoordConv

[JackKelly]

https://medium.com/@Cambridge_Spark/coordconv-layer-deep-learning-e02d728c2311

Suggested by @thecapeador

The idea being that it's really important for the CNN to discriminate between based on their location.

Several combinations to try:

• [ ] Location relative to the pixel boundaries of the image (i.e. the x and y locations of the pixels)
• [ ] The geospatial position (lat, lon)
• [ ] The clouds in the direct path between the sun and the PV system in the center of the image?!? (actually quite excited about this idea!) That is, given the Sun's azimuth and angle in the sky from the central point in the image, show the neural net where a direct line-of-sight between the Sun and the central point in the image would be, through the lower ~10 km of atmosphere (where the clouds live).

[JackKelly]

See @jacobbieker's neat implementation :) https://github.com/openclimatefix/satflow/commit/7f4d7e5397e809016b72a0f586f907fdbec7adb6