Power Flow Calculations by Deterministic Methods and Artificial Intelligence Method

Meriem Fikri, Touria Haidi, Bouchra Cheddadi, Omar Sabri, Meriem Majdoub, Abdelaziz Belfqih

Artificial Neural Networks, Fast-Decoupled Load Flow, Gauss-Seidel, Newton-Raphson, Power Flow.

In this paper, we will present different methods for Power Flow Calculations. First, we will describe the deterministic methods; which are Gauss-Seidel (GS) and Newton-Raphson (NR) methods, in addition to that, we will use also a Newton based method Fast Decoupled Load Flow (FDLF). Second, we have the Artificial intelligence method Neural Network (NN). Matlab programs were developed for solving Power Flow problem using GS and NR methods and regarding the ANN, we established and trained artificial neural networks models for computing voltage magnitudes and voltage phase angles. We used these methods to solve the Power Flow problem of the Institute of Electrical and Electronics Engineers (IEEE) 14 bus system. The results that we obtained were presented in graphs at the end of the paper.

10.22161/ijaers.5.6.25