Research on reactive power voltage control strategy of distribution networks containing distributed PV

Abstract With the large-scale increase in photovoltaic power generation, its integration into the grid will affect the system voltage of the distribution network. This paper presents a reactive voltage control strategy for the distribution network based on deep reinforcement learning. Firstly, the objective function model is established based on the node voltage and network loss of the distribution network. Secondly, each photovoltaic inverter is modeled as an agent of the enhanced learning environment. The collaborative control problem of the photovoltaic inverter is transformed into an observable Markov decision-making process through the distribution network partition. The paper uses a double delay depth deterministic gradient algorithm to solve the problem. Finally, combined with the improvement of 33 nodes for verification, the proposed strategy has the stability of improving voltage, presenting an ability to effectively reduce network loss and verify the effectiveness of the proposed strategy.