Artificial neural networks for solving the power flow problem in electric power systems

In this paper, the use of artificial neural networks (ANN) is proposed for solving the well known power flow (PF) problem of electric power systems (EPS). PF evaluates the steady state of EPS and is a fundamental tool for planning, operation and control of modern power systems. The mathematical mode...

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Bibliographic Details
Published in:Electric power systems research 2002-06, Vol.62 (2), p.139-144
Main Authors: Paucar, V.Leonardo, Rider, Marcos J
Format: Article
Language:English
Subjects:
Artificial neural networks
Electric power systems
Power flow problem
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Summary:In this paper, the use of artificial neural networks (ANN) is proposed for solving the well known power flow (PF) problem of electric power systems (EPS). PF evaluates the steady state of EPS and is a fundamental tool for planning, operation and control of modern power systems. The mathematical model of the PF comprises a set of non-linear algebraic equations conventionally solved with the Newton-Raphson method or its decoupled versions. In order to take advantage of the superior speed of ANN over conventional PF methods, multilayer perceptrons neural networks trained with the second order Levenberg–Marquardt method have been used for computing voltages magnitudes and angles of the PF problem. The proposed ANN methodology has been successfully tested using the IEEE-30 bus system.
ISSN:0378-7796
1873-2046
DOI:10.1016/S0378-7796(02)00030-5