SVD technique for estimation of harmonic components in a power system: a statistical approach

Osowski, S.

doi:10.1049/ip-gtd:19941358

Cited by 44 publications

(11 citation statements)

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“…In power system harmonics estimation, an overdetermined linear system is established in autoregressive (AR) model. Consider the signal waveform [9] x(t) = 100 cos 2π40t + 50 cos 2π217t + 40 cos 2π760t…”

Section: Harmonics Estimationmentioning

confidence: 99%

Conjugate Decomposition and Its Applications

Wang

Yuan

2013

J. Oper. Res. Soc. China

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The conjugate decomposition (CD), which was given for symmetric and positive definite matrices implicitly based on the conjugate gradient method, is generalized to every m × n matrix. The conjugate decomposition keeps some SVD properties, but loses uniqueness and part of orthogonal projection property. From the computational point of view, the conjugate decomposition is much cheaper than the SVD. To illustrate the feasibility of the CD, some application examples are given. Finally, the application of the conjugate decomposition in frequency estimate is given with comparison of the SVD and FFT. The numerical results are promising.

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Section: Harmonics Estimationmentioning

confidence: 99%

Conjugate Decomposition and Its Applications

Wang

Yuan

2013

J. Oper. Res. Soc. China

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“…To improve placement quality, a suitable procedure to perform HSE such as singular value decomposition (SVD) which s a useful tool for this task, should be defined [16][17][18][19][20][21]. One of the advantages of SVD approach is that it does not require the whole network system to be observable prior to estimation.…”

Section: Introductionmentioning

confidence: 99%

Power quality meters placement using seeker optimization algorithm for harmonic state estimation

Ketabi

Sheibani

Nosratabadi

2012

International Journal of Electrical Power & Energy Systems

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“…Using eigenvalue analysis, the smallest eigenvalue of the admittance matrix is observed [4]. By means of the analysis, it is possible to determine changes of the smallest eigenvalue with frequency as well as changes of bus participation factors with resonance modes [5].…”

Section: Introductionmentioning

confidence: 99%