Power system harmonic and interharmonic estimation using Vortex Search Algorithm

Altintasi, Cagri; Aydın, Ömer; Taplamacıoğlu, M. Cengiz; Salor, Özgül

doi:10.1016/j.epsr.2019.106187

Cited by 22 publications

(14 citation statements)

References 19 publications

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“…In this study, it is assumed that the frequencies of the signal are not known, unlike other heuristic based methods in the literature [13][14][15][16][17][18][19][20][21]. Therefore, the mathematical model defined in [13][14][15][16][17][18][19] has no significance in this study.…”

Section: Exp( )mentioning

confidence: 99%

“…In recent years, the use of optimization algorithms for solving the engineering problems has been increasing [11][12]. Many hybrid optimization methods have also been applied for the harmonic analysis [13][14][15][16][17][18][19][20][21][22]. The amplitude and phase values of harmonics and sub-inter-harmonics estimated in [13][14][15][16] are more 5% of the actual values, which is higher than the maximum error rate specified in the standard [5].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, in these hybrid methods, while phase estimation is performed with heuristics algorithm, Recursive Least Square (RLS) or KF is used for amplitude estimation, which has disadvantages previously stated for KF. In [20][21][22], the authors estimated the amplitudes and phases estimation directly with the optimization algorithm without using a hybrid method.…”

Section: Introductionmentioning

confidence: 99%

“…In all optimization-based algorithms [13][14][15][16][17][18][19][20][21][22] that are based on KF or RLS, the amplitude and phase estimation is performed by assuming that the frequency of harmonic or sub-inter-harmonic components contained in the signal to be estimated are known. However, in real power systems, if the fundamental frequency and the frequencies of other harmonics and sub-inter-harmonics are not at their nominal values, then the amplitude and phase estimations made by these methods will be false.…”

Section: Introductionmentioning

confidence: 99%

“…In this study, unlike harmonic analysis using optimization-based algorithms in the literature [13][14][15][16][17][18][19][20][21][22], it is assumed that the frequencies of the harmonic or interharmonic components of the signal are not known. The performance of the SCA has been tested in cases, where the signal contains harmonic and inter harmonic components, at different signal-to-noise ratios (SNR).…”

Section: Introductionmentioning

confidence: 99%

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Sine Cosine Algorithm Approaches for Directly Estimation of Power System Harmonics & Interharmonics Parameters

Altintasi

2021

IEEE Access

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In order to maintain the power quality, parameters of harmonic and sub-inter-harmonic components in the signal must be estimated accurately with less computational complexity. In power systems, the value of fundamental frequency changes between 49.5Hz and 50.5Hz and this situation causes the frequency of other harmonic components to change. In order to make efficient amplitude and phase estimation, initially, frequencies must be estimated properly. In this study, the Sine Cosine Algorithm is applied for the estimation of harmonics and sub-inter-harmonics parameters in the power systems. Unlike other optimization-based methods in the literature, it is assumed that the frequencies of the harmonic and sub-inter-harmonics component in the signal are not known. The proposed algorithm has been tested on synthetic signals at different noisy environment. Given the results obtained, SCA can predict the frequencies, amplitudes, and phases of harmonics and sub-inter-harmonics with less than 5% error, which is the maximum error limit specified by the standard, and proposed algorithm estimates the actual parameters with a low error rate even in noisy environments. In addition, SCA has a better convergence performance index than optimization algorithms used in studies in the literature assuming that frequency is known. Performance of the proposed algorithm is also tested on the data obtained from electrical transmission system. SCA estimates the frequencies of harmonics with almost no error, and the amplitude and phase estimation values of each harmonic are in corroboration with the results obtained by the DFT method.

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