  Solar PV yield nowcasting is used to help anticipate peaks and troughs in
demand to support grid integration. This paper compares multiple low-resource
approaches to nowcasting solar PV yield, using a dataset of UK satellite
imagery and solar PV energy readings over a 1 to 4-hour time range. The paper
also estimates the carbon emissions generated and averted by deploying models,
and finds that even small models that could be deployable in low-resource
settings may have a benefit several orders of magnitude greater than its carbon
cost. The paper also examines prediction errors and the activations in a CNN.
