Particle Swarm Optimization- Artificial Neural Network For Power System Load Flow

Abstract

Load flow study is done to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state working condition of a power system. It is important and most frequently carried out study performed by power utilities for power system planning, optimization, operation and control. In this paper a Particle Swarm Optimization Neural Network (PSO-ANN) is proposed to solve load flow problem under different loading/ contingency conditions for computing bus voltage magnitudes and angles of the power system. A multilayered feed-forward neural network is trained by using PSO technique. The results show the effectiveness of the proposed PSO-ANN based approach for solving power flow problem having different loading conditions and single-line outage contingencies in IEEE 14 bus system