USING ARTIFICIAL NEURAL NETWORK TO CALCULATE STEADY STATE CONDITIONS

The power systems steady-state problem are described by a system of nonlinear equations, and for their solution are widely used iterative techniques such as the Newton-Raphson and others. Recently, techniques based on the use of genetic algorithms, the theory of fuzzy sets, artificial neural networks have been applied to solve this problem. In this article feedforward neural networks are used for calculating the steady-state regimes. The modeling results were obtained with the results of calculations using the Newton-Raphson method