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.
@article{arxiv.2210.04554,
title = {Comparing the carbon costs and benefits of low-resource solar nowcasting},
author = {Ben Dixon and María Pérez-Ortiz and Jacob Bieker},
journal= {arXiv preprint arXiv:2210.04554},
year = {2022}
}