Solar Power Ensemble Forecaster

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Accurately forecasting the output of grid connected solar systems is critical to increasing the overall penetration of solar and renewables on the electrical network. This is important for the stability and management of the electrical system as a whole.The electrical output of solar panels is significantly impacted by cloud cover. Clouds can move and form very quickly, and it is important to monitor and predict the impact of cloud cover.This project will implement a short-term solar forecasting system on five operational solar farms. The farms are spread from far north Queensland to Victoria. These sites represent meteorologically diverse locations that will experience widely varied weather conditions and cloud types over the 18-month project trial period.The forecasting technology will integrate five state-of-the-art short-term solar forecasting models into a single optimised ensemble model. The purpose of the ensemble model is to capitalise on the strengths of each of the established forecasting technologies to produce an industry best practice forecast.Technologies range from skyward facing cameras utilising machine vision algorithms to track and predict cloud motion, satellite imaging based cloud motion vector modelling, statistical auto-regression models, numerical weather predictions and detailed power conversion models.

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