Machine Learning for Sustainability at Edison: Renewable Energy Forecasting

Date:

Wednesday, November 15, 2023

Time:

2:00 pm

Room:

Bernstein

Summary:

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.

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