Abstract
Practical successes have been achieved with neural network models in a variety of domains, including energy-related industry. The large, complex design space of electrical power systems (EPS) is only minimally explored in current practice. The satisfactory results that nevertheless have been obtained testify that neural networks are a robust modeling technology; at the same time, however, the lack of a systematic design approach implies that the best neural network models generally remain undiscovered for most applications. This chapter presents an approach to an adaptive protective systems problem in complex power generating units. First, we demonstrate the complex interdependencies between various parameters of EPS protection systems. Then, we present an approach, based on protection and adaptation criteria, for designing a neural network based adaptive protection system.
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© 2002 Springer-Verlag Berlin Heidelberg
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Halinka, A., Sowa, P., Szewczyk, M., Sztandera, L.M. (2002). Neural Network-Based Adaptive Protection System. In: Soft Computing in Industrial Electronics. Studies in Fuzziness and Soft Computing, vol 101. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1783-6_6
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DOI: https://doi.org/10.1007/978-3-7908-1783-6_6
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-2513-8
Online ISBN: 978-3-7908-1783-6
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