Modification of the methodology to determine the maximum values of transfer capability of network elements

The development of digital technologies and the introduction of intelligent technique of energy system control into the operational dispatch management system significantly increases the efficiency of control of electric power modes. At the same time, new technologies are tightening the requirements for the quality, speed of receiving and processing information, especially in pre-emergency, emergency, post-emergency and forced modes of operation of the energy system. Thus, for effective control in a forced mode, i.e. when the load is higher than the nominal parameters, but lower than the maximum admissible limits, current data on the actual value of the transmission line capacity range is required considering the restrictions for a specific time. The purpose of the study is to test an artificial neural network for a high-speed method of updating data on the value of the maximum transfer capability of network elements. The study has been carried out using optimization methods, simulation of electrical network operation modes, artificial neural networks and methods for operating mode estimation. A method for adaptive capacity assessment has been developed. An automated control system for power flows in forced mode has been synthesized. It has been established that the use of an artificial neural network significantly increases the speed of calculating the actual value of transfer capacity due to the use of measurements for the time being. The accuracy of the permissible flow is acceptable and is configured by adjusting the weight coefficients of the neural network. The method to determine the actual value of the transfer capability of a network element based on an artificial neural network is an effective means to accurately calculate the transfer capability for the time being.