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Performance assessment of iterative linear methods for the computation of the power flow problem solution

Fernandes A. A., Freitas F. D., Ishihara J. Y.

Przegląd Elektrotechniczny

2015

R. 91, nr 9

254-258

This paper investigates the use of iterative linear methods applied to the power flow problem (PFP) solution in power systems. Preconditioning techniques are studied and incorporated to the methodology to solve a linear system. As application to the PFP, four iterative linear techniques and a direct method are evaluated and their performances are compared. Numerical experiments demonstrate the effectiveness of the proposed methodology, suggesting the good performance of the Bi-conjugate Gradient Stabilized (BiCGStab) as an adequate iterative linear method for the applicability in the solution of a PFP.

W artykule analizowano metodę iteracyjną zastosowaną do kontroli przepływów mocy. Zbadano cztery liniowe techniki iteracyjne i metodę bezpośrednią Najlepsze właściwości wykazała technika Bi-conjugated Gradient Stabilized BiCGStab.

Computationally effective algorithm to the epsilon -insensitive fuzzy clustering

Łęski J.

Systems Science

2002

Vol. 28, nr 3

31-50

The fuzzy c-means method is one of the most popular clustering methods based on minimization of a criterion function. However, one of the greatest disadvantages of this method is its sensitivity to the presence of noise and outliers in data. The epsilon -insensitive Fuzzy C-Means ( epsilon FCM) clustering algorithm is free of this disadvantage, but has a very high computational burden and requires a choice of the insensitivity parameter(s) epsilon In this paper, a new computationally effective epsilon -insensitive fuzzy c-means clustering algorithm with automatic adjustment of the insensitivity parameter(s) is introduced. Performance of the new clustering algorithm is experimentally verified using synthetic data with outliers and overlapped groups of heavy-tailed data.