ABSTRACT With the rapid increase in penetration of distributed generation predominantly based on renewable energy sources within distribution networks, the inherent volatility and intermittency of distributed generation exacerbate voltage fluctuations and uneven voltage profiles. Concurrently, insufficient coordination mechanisms for diverse controllable devices lead to frequent limit violations of automatic voltage control actions at substations, causing significant voltage control challenges. To address these issues, this study proposes a reactive power voltage control method for distribution networks based on a ‘network partitioning and distributed scheduling’ process. First, the affinity propagation clustering algorithm is employed to partition the network based on the reactive power‐voltage sensitivity matrix. Subsequently, a Markov game model is formulated for voltage control within each partition and the twin delayed deep deterministic policy gradient algorithm is utilised for a distributed solution, outputting target reactive power setpoints for both distributed generators and static Var compensators. Compared to conventional real‐time control methods, the proposed approach significantly reduces the dependence on centralised communication infrastructures and achieves autonomous regional control of reactive power and voltage. Consequently, it effectively minimises the frequency of automatic voltage control corrective actions and enhances the robustness of voltage control. Finally, the effectiveness of the proposed methodology is validated through simulation case studies utilising the IEEE 33‐bus test system and a real‐world network model based on the Beijing distribution grid.
Yang et al. (Thu,) studied this question.