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Found 3 papers, 1 papers with code
Optimal Scheduling of Electric Vehicle Charging with Deep Reinforcement Learning considering End Users Flexibility
The rapid growth of decentralized energy resources and especially Electric Vehicles (EV), that are expected to increase sharply over the next decade, will put further stress on existing power distribution networks, increasing the need for higher system reliability and flexibility.
Solar Power driven EV Charging Optimization with Deep Reinforcement Learning
Power sector decarbonization plays a vital role in the upcoming energy transition towards a more sustainable future.
ELECTRIcity: An Efficient Transformer for Non-Intrusive Load Monitoring
Sequence-to-sequence deep learning models have been firmly established as state-of-the-art approaches for NILM, in an attempt to identify the pattern of the appliance power consumption signal into the aggregated power signal.
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