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Estimating electricity saving-potential in small offices using adaptive thermal comfort
The smart control informed by IoT sensors and enabled by remotely controlled devices can optimize the building operation to minimize unnecessary energy consumption and improve indoor thermal comfort.
Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning
In this paper, we mitigate these limitations by developing a novel deep meta reinforcement learning (DMRL) algorithm.
Accelerated Deep Reinforcement Learning Based Load Shedding for Emergency Voltage Control
Load shedding has been one of the most widely used and effective emergency control approaches against voltage instability.
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