Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Grids. (arXiv:2005.01979v2 [cs.LG] UPDATED)

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 …

actor-critic arxiv learning lg scheduling smart