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Computationally efficient joint coordination of multiple electric vehicle charging points using reinforcement learning.

, , and . CoRR, (2022)

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Computationally efficient joint coordination of multiple electric vehicle charging points using reinforcement learning., , and . CoRR, (2022)Optimized cost function for demand response coordination of multiple EV charging stations using reinforcement learning., , and . CoRR, (2022)Real-world user flexibility of energy consumption: two-stage generative model construction., , and . SAC, page 2148-2153. ACM, (2016)Definition and Evaluation of Model-Free Coordination of Electrical Vehicle Charging With Reinforcement Learning., , and . IEEE Trans. Smart Grid, 11 (1): 203-214 (2020)Reduced state space and cost function in reinforcement learning for demand response control of multiple EV charging stations., , and . BuildSys@SenSys, page 344-345. ACM, (2019)Quantifying flexibility in EV charging as DR potential: Analysis of two real-world data sets., , , and . SmartGridComm, page 600-605. IEEE, (2016)Achieving Scalable Model-Free Demand Response in Charging an Electric Vehicle Fleet with Reinforcement Learning., , and . e-Energy, page 411-413. ACM, (2018)Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning., , and . CoRR, (2018)Modeling Real-World Flexibility of Residential Power Consumption: Exploring the Cylindrical WeiSSVM Distribution., , , and . e-Energy, page 408-410. ACM, (2018)