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
Singh, Avnish; Dixit, Shishir; and Srivastava, Laxmi
"Particle Swarm Optimization- Artificial Neural Network For Power System Load Flow,"
International Journal of Power System Operation and Energy Management: Vol. 1
, Article 5.
Available at: https://www.interscience.in/ijpsoem/vol1/iss3/5