… match the continuous power control problem. Hence, this paper provides a deep deterministic
policy gradient (DDPG) scheme for power control. A power selection policy designated an …

… Policy Gradient (DDPG) into the dynamic power control … , we investigate the optimal power
control strategy in EH-UDN … the optimization framework of the power control scheme. In …

… power system stabilizers (PSSs) are typically employed. These facilities generate auxiliary
control … deep deterministic policy gradient (DDPG) based on a synergetic control approach to …

… In this paper, we present two novel approaches based on deep deterministic policy gradient
… policy gradient” and “sharing deep deterministic policy gradient”, for the multi-agent power …

… execution, computation of the reward is not required - since we will focus on a policy
gradient RL algorithm. Thus, knowledge of i E t r e q and i T t d e p is not required during policy …

… and the corresponding optimal reactive power control (aka, policy) is parameterized in the
… power loss over a number of historical and simulated training pairs, using the policy gradient …

… Since TD3, which policy gradient methods used, is well known as a model to avoid the
curse of dimensionality, although their units are not the same, TD3 algorithm does not need a …

… This section introduces the power control method based on the deep deterministic policy
gradient (DDPG) algorithm, which is used to achieve the power control objectives of the WPGS. …

… of policy gradient reinforcement learning methods, using artificial neural networks for policy
function … The methods are compared using an AC optimal power flow based power exchange …

… (4)) to a continuous action space is problematic, as the greedy policy requires global
optimization during policy improvement. The deterministic policy gradient (DPG) is more …