Optimization of electric power system modes by methods of artificial intelligence

One of the tasks of optimization is to choose from the number of possible solutions the solutions providing for the values of the managed parameters to meet the specified restrictions and turn the target function into a maximum or minimum. The choice of the most rational algorithm for optimizing the power system mode is an important task since in order to control the modes using a computer in real-time, it is necessary to ensure high performance of programs that implement the algorithm. This speed depends not only on the speed of computer calculations but also on the mathematical method embedded in the algorithm. Moreover, various methods differ in the amount of intermediate information stored, which is also important when developing optimization programs. This study analyzes the basic normal mode currently implemented in the electric power system of Mongolia by means of RastrWin and ANARES software systems. Adding a new high-power traction load resulted in a shortage of active power in the system. For this reason, the study of VAR optimization of the electric power system mode with the implementation of the particle swarm algorithm has been carried.