  This letter investigates a Branching Dueling Q-Network (BDQ) based online
operation strategy for a microgrid with distributed battery energy storage
systems (BESSs) operating under uncertainties. The developed deep reinforcement
learning (DRL) based microgrid online optimization strategy can achieve a
linear increase in the number of neural network outputs with the number of
distributed BESSs, which overcomes the curse of dimensionality caused by the
charge and discharge decisions of multiple BESSs. Numerical simulations
validate the effectiveness of the proposed method.
