Real-Time Energy Management of PV-ESS Integrated Active Distribution Networks Using Digital Twin-Enabled Deep Reinforcement Learning
The proposed DT-DRL framework establishes a closed-loop cyber–physical architecture in which continuously synchronized Digital Twin states are directly incorporated into a Proximal Policy Optimization (PPO)-based decision-making process to jointly minimize operating cost, voltage deviation, and battery degradation while satisfying network operational constraints.