Probability-statistical approach development to the survivability increacing of power plant auxiliary grid

The object of research is the operating modes and ways to increase the survivability of the power plant's own needs network under the influence of external emergency disturbances. The power system of Ukraine today operates in extremely complex conditions. This is a consequence of the fact that the existing problems associated with outdated equipment have been added by external destructive influence due to geopolitical events. These factors cause a decrease in the structural and regime reliability of electrical networks. Under such conditions, the survivability of power plants and their own needs systems becomes of particular importance. The task of increasing the survivability of the power plant's own needs network is one of the multi-criteria tasks with a large number of uncertainties. To solve it, it is advisable to apply a probabilistic-statistical approach that takes into account the available random factors and makes it possible to make effective decisions. In the course of the research, an approach to assessing the survivability of the power plant's own needs network using a random number generator was developed, and the effectiveness of measures to increase it was determined. This approach allows for a quantitative assessment of the survivability of the power plant's own needs network under conditions of uncertainties associated with the network and surrounding power system modes. The approach also takes into account the probability of equipment failure over a time interval and the consequences of geopolitical influence on the power system of Ukraine. The risk of an emergency situation occurring in the power plant's own needs network is taken as a quantitative criterion for assessing survivability. The developed approach and its implementation algorithm allow for a comparative analysis of the effectiveness of measures to increase the survivability of the power plant's own needs network and to select the most effective ones among them. According to the results of probabilistic and statistical modeling of the HPP's own needs network, it was determined that when using survivability measures, the risk of an emergency situation is reduced by 32%.