Abstract
In this paper we consider the problem of power system stability with an application of predictive control systems, and in particular control systems which rely on Neural Networks to maintain system stability. The work focuses on how a hybrid control system utilizing neural networks has the capabilities to improve the stability of an electric power grid when used in place of traditional control systems, i.e. PID type controllers. Testing is done using simulation of the dynamical system with the different control schemes implemented, resulting in a measure of stability through which the controllers can be justified.
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© 2003 Springer-Verlag Berlin Heidelberg
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Ball, S. (2003). Neural Network Predictive Control Applied to Power System Stability. In: Abraham, A., Franke, K., Köppen, M. (eds) Intelligent Systems Design and Applications. Advances in Soft Computing, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44999-7_5
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DOI: https://doi.org/10.1007/978-3-540-44999-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40426-2
Online ISBN: 978-3-540-44999-7
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