An Improved ANN–BPN to Radial Distribution System Load Flow - Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE-2012) - page 182

An Improved ANN-BPN to Radial
Distribution System Load Flow
Vaishali Holkar and Deepika Masand
Abstract This paper shows an application of artificial neural networks (ANNs) to
determine the bus voltages and phase angles of a radial distribution system,
without executing the load flow algorithm, for any given load. The performance of
the conventional load flow methods such as Newtoh—Raphson load flow, Fast
decoupled load flow is found to be very poor under critical conditions, such as high
R/X ratio, heavily loading condition, etc. To overcome the limitations of these
regularly used methods a simple and reliable ladder iterative technique is used for
solving the power balance equations of radial distribution system (RDS). The
proposed method makes use of a multilayer feed forward ANN with error back
propagation learning algorithm for calculation of bus voltages and its angles.
A sample IEEE 33-bus is extensively tested with the proposed ANN-based
approach indicating its viability for RDS load flow assessment and results are
presented.
Keywords Ladder iterative technique R/X ratio Artificial neural networks
(ANNs) Backpropagation network (BPN) Radial distribution system (RDS)
Forward sweep Backward sweep
V. Holkar ( & )
Department of Electrical and Electronics Engineering, Oriental Institute of Science
and Technology, R.G.P.V, Bhopal, MP, India
e-mail: [e-mail]
D. Masand
Head of Department of Electrical and Electronics Engineering, Oriental Institute of Science
and Technology, R.G.P.V, Bhopal, MP, India
e-mail: [e-mail]