PARALLEL SELF-ORGANIZING HIERARCHICAL NEURAL-NETWORK-BASED FAST VOLTAGE ESTIMATION

Fast voltage security monitoring and analysis have assumed importance in the present-day stressed operation of power system networks; and fa st prediction of bus voltage is essential for this. An approach based on parallel self-organising hierarchical neural networks is presented to predict bus voltage in an efficient manner. Parallel self-organisin g hierarchical neural networks (PSHNN) are multistage networks, in whi ch stages operate in parallel rather than in series during testing, Th e entropy concept has been used to identify the inputs for PSHNN. A re vised back propagation algorithm is used for learning input nonlineari ties, along with forward-backward training. The proposed method is use d to predict bus voltage at different loading conditions and for an ou tage event in IEEE 30-bus and a practical 75-bus systems.