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This page is about the applications of machine learning (ML) in the context of power system simulation and optimization. For an overview of power system optimization more generally, please see the Wikipedia page on this topic.
Scheduling algorithms on the power grid have trouble handling large quantities of solar, wind, and other time-varying electricity sources. ML can help improve electricity scheduling algorithms, control storage and flexible demand, and design real-time electricity prices that reduce CO2 emissions.