The aim of this research was the optimal management of overvoltage in the photovoltaic system with the aim of maintaining voltage stability and reducing network losses. In the simulation process, we considered the number of buses and 10 scattered production sources as the path and simulation process. We considered the number of 10 scattered production sources with a capacity between 18 and 25 MW. Examining the preliminary results of the system has shown that the range is low Medium and high stability is considered based on the distance between each bus with scattered production sources. So that basses 1 to 3 have the lowest range of oscillation because they are located in the closest distance to the production sources. Similarly, basses 7 to 17 have more distances than the production source and have more fluctuation. In order to meet the needs of the network for optimumThe distribution of the production of scattered production sources, which usually have non-constant conditions, especially from bus 7 onwards, it is possible to observe the amount of waste in the network due to the lack of coordination of the scattered production with the network demand, we used the optimal management of overvoltage . The amount of overvoltage of each distributed generation source varies from 25 MW to 18 MW and in each bus this requirement is investigated in the network. and the measurement has been placed. This optimal distribution rate was matched with the amount of consumption and demand of the network in overvoltage and we showed that, for example, in the first bus, the amount of demand of the network is 800 megawatts and the amount of production of the main network in overvoltage is equal to 770 megawatts and a deficit of 30 megawatts has been observed. Using the optimal management of overvoltage of 25 megawatts of the entire networkFrom scattered productions, the power is transferred with this bus to compensate the deficit to a large extent. In the following, in order to formulate an optimal management model for overvoltage distribution, the establishment of a balance point for the activity of network buses along with the ten sources of distributed generation has been investigated. For this purpose, by categorizing all network buses into four modes that include all buses, each mode (average We compared multiple bus sets) in each bus and showed that in the first bus and the first mode, the optimization rate of overvoltage control management was equal to 68.73% and in one turn, not considering the first mode for the bus network and only in Considering the fourth mode, which includes buses 7 to 17, the amount of network optimization has increased by 11.71%. In other words, in the fourth mode Without having six buses, we were able to optimize the network by 11.71% with the help of overvoltage control management.