large scale integration of distributed photovoltaic (PV) systems poses considerable challenges to voltage regulation in distribution networks.A real time voltage control approach utilizing robust reinforcement learning is proposed to alleviate the effects of measurement uncertainty.First

a voltage control model for distribution networks is established to minimize voltage deviation

subsequently reformulated as a Markov decision process.Secondly

a distur bance agent is introduced to induce perturbations in the observation state

so imitating measurement inaccuracies.Finally

a framework combining synchronous training and asynchronous learning is developed to improve the agents robustness.The simulation findings for the IEEE 33 bus system indicate that the proposed solution is both effective and reliable.