Clean Power Professionals Group
This special interest group is for professionals to connect and discuss all types of carbon-free power alternatives, including nuclear, renewable, tidal and more.
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Leveraging Machine Learning and Optimization for Renewable Energy
📰 I present 3 renewables use cases for Vattenfall, Ørsted and #Britain, in which Machine Learning and Quantitative Optimization help
1️⃣ improve energy yield up to 10%,
2️⃣ predict (with 99% accuracy) the potential of new wind farm sites,
3️⃣ save millions of tons of CO2 per year, and
4️⃣ demonstrate how Britain's domestic transport demand can be met by renewables only.
Leveraging Machine Learning and Optimization for Renewable Energy
🔎 I argue whether Denmark's prominence in using wind energy can be explained by its 2 big players' (Vattenfall and Ørsted) maturity in leveraging QO and ML techniques. 🎯 Machine Learning (ML) and Quantitative Optimization (QO) methods do not compete with each other as they are complementary techniques. 📈 While ML can help predict new situations, QO finds the best solution out of trillions of alternatives. 💰They are the easiest and cheapest enablers of integrating decarbonized energy sources into our lives. #energy #renewables #renewables #machinelearning #utilities #windenergy #hydrogen #windfarmlayoutoptimization #optimization #algorithms #mathematicalmodeling #power #ai #renewableenergy #ml #artificialintelligence
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