SAC-based Voltage control in Active Distribution Network with Renewable Energy Resource

In active distribution network, the high share of distributed photovoltaic (PV) integration raises the potential for voltage violations within (ADN), and classical model-driven voltage control methods rely heavily on precise physical parameters, which are hard to be adopted in practice. This paper presented an innovative data-driven approach to voltage control. To achieve well-managed energy storages (ESs) and static var compensators (SVCs), the optimization problem with system power loss and voltage constraint is modeled as a Markov Decision process (MDP), which is resolved utilizing a soft actor critic (SAC) reinforcement learning algorithm. The suggested voltage control mechanism is also evaluated in the IEEE 33-node distribution network for validity and feasibility.