Wavelet Analysis and Radial Basis Function Neural Network Based Stability Status Prediction Scheme

Autor:	Emmanuel Asuming Frimpong, Philip Yaw Okyere, Johnson Asumadu
Jazyk:	English<br />Indonesian
Rok vydání:	2018
Předmět:	Radial basis function Transient analysis and Wavelet transform Transient analysis Wavelet transform Electrical engineering. Electronics. Nuclear engineering TK1-9971
Zdroj:	Jurnal Nasional Teknik Elektro, Vol 7, Iss 3, Pp 146-152 (2018)
Druh dokumentu:	article
ISSN:	2302-2949 2407-7267
Popis:	This paper presents a technique for predicting the transient stability status of a power system. Bus voltages of system generators are used as input parameter. The bus voltages are processed using wavelet transform. Daubechies 8 mother wavelet is employed to extract wavelet entropy of detail 1 coefficients. The sum of wavelet entropies is used as input to a trained radial basis function neural network which predicts the transient stability status. The IEEE 39-bus test system was used to validate the effectiveness and applicability of the technique. The technique is simple to apply and can be implemented in real-time. The prediction accuracy was found to be 86.5% for 200 test cases.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/f8be1c53762547678a94becdca010f67 Zobrazit plný text záznamu View record in DOAJ