Renewable energy dependence on fluctuating weather conditions may prevent a fast energy transition. Since 2013, Edison have developed custom algorithms for wind and solar forecasting, moving from proprietary tools to open-source libraries, from on-premises architecture to MLOps cloud infrastructure. This case study is aimed at data scientists and MLOps engineers willing to deal with a huge number of models. You will learn how ML/AI can boost renewable energy penetration in the market.