Load flow solution using neuro-fuzzy techniques

Abstract

Load-flow (LF) study is the steady state solution of the power system network under existing or contemplated conditions for normal operation. In this paper, a neuro-fuzzy system is proposed to solve power flow problem under different loading/contingency conditions for computing bus voltage magnitudes and angles of the power system. The neuro-fuzzy system combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The composition of the input variables for the proposed neural network has been selected to emulate the solution process of a conventional power flow program. The effectiveness of the proposed neuro-fuzzy based approach for solving power flow is demonstrated by computation of bus voltage magnitudes and voltage angles for different loading conditions and single line-outage Contingencies in IEEE 30-bus system.