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Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Grids. (arXiv:2005.01979v2 [cs.LG] UPDATED)
Aug. 24, 2022, 1:12 a.m. | Joash Lee, Wenbo Wang, Dusit Niyato
stat.ML updates on arXiv.org arxiv.org
We consider the problem of demand-side energy management, where each
household is equipped with a smart meter that is able to schedule home
appliances online. The goal is to minimize the overall cost under a real-time
pricing scheme. While previous works have introduced centralized approaches in
which the scheduling algorithm has full observability, we propose the
formulation of a smart grid environment as a Markov game. Each household is a
decentralized agent with partial observability, which allows scalability and
privacy-preservation …
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