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Researchers at the University of California, Santa Cruz have tested the use of machine learning to optimize power restoration on microgrids after power outages. Microgrids are small-scale power grids that often include renewable energy sources and can be as small as a group of residential buildings with solar panels. Deep reinforcement learning was used to manage the load restoration process in bringing a microgrid back online after a power loss. Practical constraints such as the cost of running fuel-powered generators and the fluctuating availability of renewable energy make it a complex optimization problem.
