Deep Reinforcement Learning for Optimal Power Flow with Renewables Using Graph Information. (arXiv:2112.11461v2 [cs.LG] UPDATED)

Renewable energy resources (RERs) have been increasingly integrated into
large-scale distributed power systems. Considering uncertainties and voltage
fluctuation issues introduced by RERs, in this paper, we propose a deep
reinforcement learning (DRL)-based strategy leveraging spatial-temporal (ST)
graphical information of power systems, to dynamically search for the optimal
operation, i.e., optimal power flow (OPF), of power systems with a high uptake
of RERs. Specifically, we formulate the OPF problem as a multi-objective
optimization problem considering generation cost, voltage fluctuation, and
transmission …

arxiv flow graph information learning lg power reinforcement reinforcement learning renewables