An interview with Vestas, Utopus Insights and Infigen regarding the short-term forecasting trial at Infigen Energy’s Lake Bonney 2 and 3 wind farms.
Interview extract
What were the key drivers for Vestas to demonstrate the ability to self-forecast?
Vestas: Self-forecasting in the National Electricity Market (NEM) provides semi-scheduled generators with the opportunity to more accurately predict their electricity production and more closely meet their dispatch target. By doing so, they can reduce their exposure to Frequency Control Ancillary Services (FCAS) ‘Causer Pays’ costs and contribute to stabilising the grid. Across Australia and New Zealand, Vestas currently services 3.7 GW worth of projects. Within a focus on the NEM, Vestas is positioned to play a key role in shaping a grid that is less reliant on FCAS and better equipped to absorb more renewables in its energy mix. Equally important is improving the business cases of renewable asset owners in the NEM, which we hope will lead to further investment in renewables, lower power prices for consumers and ultimately a reduction in carbon emissions.
UTOPUS INSIGHTS: Utopus Insights used the self-forecasting trial under ARENA’s Advancing Renewables Program, as an opportunity to explore and push the boundaries of Machine Learning by making renewable energy production forecasting as accurate as possible. The team strived to make renewables more dispatchable in the power market, and to improve the accuracy of five-minute forecasting, which is going to be increasingly important in the coming years, not only in this region, but worldwide.
Self-forecasting is a clear fit in our mission to deliver digital solutions to Independent Power Producers (IPPs), farm owners and operators to maximize asset output. The ability to self-forecast helps renewable power producers minimize their exposure to financial penalties associated with 5 minute intermittent resource forecast requirements, which we have now proved to be among our strongest digital solution service offering.