This project aims to provide an efficient and robust method for solar power generation predictions for newly established farms that have few or no historical data.
By leveraging data from established solar plants and employing Artificial Intelligence (AI) algorithms, the method will extrapolate and adapt patterns from these data-rich environments to make accurate predictions for the new solar plant.
January 2023 to December 2023
Acknowledgement of Country
RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.
Acknowledgement of Country
RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business.