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.