Forecasting regional PV power in Great Britain with a multi-modal late fusion network (Papers Track)

James Fulton (Open Climate Fix); Jacob Bieker (Open Climate Fix); Peter Dudfield (Open Climate Fix); Solomon Cotton (Open Climate Fix); Zakari Watts (Open Climate Fix); Jack Kelly (Open Climate Fix)

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Power & Energy Computer Vision & Remote Sensing


The ability to forecast solar photovoltaic (PV) power is important for grid balancing and reducing the CO2 intensity of electricity globally. The use of multi-modal data such as numerical weather predictions (NWPs) and satellite imagery can be harnessed to make more accurate PV forecasts. In this work, we propose a late fusion model which integrates two different NWP sources alongside satellite images to make 0-8 hour lead time forecasts for grid regions across Great Britain. We limit the model inputs to be reflective of those available in a live production system. We show how the different input data sources contribute to average error at each time horizon and compare against a simple baseline.

Recorded Talk (direct link)