Optimal estimation of power system harmonics using a hybrid Firefly algorithm-based least square method

Singh, Santosh Kumar; Sinha, Nilotpal; Goswami, Arup Kumar; Sinha, Nidul

doi:10.1007/s00500-015-1877-0

Cited by 19 publications

(6 citation statements)

References 16 publications

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“…In this section, a synthetic signal, based on the one used in [24,25], is studied. This signal represents a typical industry waveform, which comprises the effects of power electronic devices, Variable Frequency Drives (VFDs), and arc furnaces.…”

Section: Sk Vs Dft In the Harmonic Evaluationmentioning

confidence: 99%

Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

et al. 2019

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The highly-changing concept of Power Quality (PQ) needs to be continuously reformulated due to the new schemas of the power grid or Smart Grid (SG). In general, the spectral content is characterized by their averaged or extreme values. However, new PQ events may consist of large variations in amplitude that occur in a short time or small variations in amplitude that take place continuously. Thus, the former second-order techniques are not suitable to monitor the dynamics of the power spectrum. In this work, a strategy based on Spectral Kurtosis (SK) is introduced to detect frequency components with a constant amplitude trend, which accounts for amplitude values’ dispersion related to the mean value of that spectral component. SK has been proven to measure frequency components that follow a constant amplitude trend. Two practical real-life cases have been considered: electric current time-series from an arc furnace and the power grid voltage supply. Both cases confirm that the more concentrated the amplitude values are around the mean value, the lower the SK values are. All this confirms SK as an effective tool for evaluating frequency components with a constant amplitude trend, being able to provide information beyond maximum variation around the mean value and giving a progressive index of value dispersion around the mean amplitude value, for each frequency component.

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Section: Sk Vs Dft In the Harmonic Evaluationmentioning

confidence: 99%

Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

et al. 2019

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“…The selection of mother wavelet is a major challenge and plays a very important role in the detection and classification [31,32]. There are various wavelets used in signal processing such as Daubechies, Symlets, Coiflets and Haar wavelets.…”

Section: Case 5: Comparison To Wtmentioning

confidence: 99%

Double‐ended travelling‐wave fault location based on residual analysis using an adaptive EKF

Yang

Zhang

et al. 2018

IET signal process.

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This paper presents the estimated residuals for detecting the traveling wave front using an adaptive extended Kalman filter based on the maximum likelihood (EKF-ML), which uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. In some situations, such as faults close to the bus or close to zero inception angle, or faults with high fault resistances, the transient waves can become weak and even become lost in the noise, which makes the discrimination of the traveling wave front become more difficult. Aiming at this, residuals between the observed values and the estimated values using the adaptive EKF exhibit remarkable singularities, and can be used for exactly determining the wave front. Thus, the exact arrival time of the initial wave head can be determined and then the fault distance can be calculated precisely. The effectiveness of exacting mutation feature using the proposed method has been demonstrated by a simulated instantaneous pulse. And it has been tested with different types of faults using ATP simulation. Simulation results verify that the estimated residuals are highly sensitive to traveling wave front and less sensitive to modeling uncertainty (such as noise disturbance).

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“…Hung applied FA in OFDM systems [29] and Kamarian et al used FA for thermal buckling optimization of composite plates [32], while Jafari and Akbari used FA to optimize micrometre-scale resonator modulators [31], and Othman et al used a supervised FA to achieve optimal placement of distributed generators [49]. Also, Singh et al combined FA with least-squares method to estimate power system harmonics [61], and Kaur and Ghosh used a fuzzy FA for network reconfiguration of unbalanced distribution networks [34].…”

Section: Applications Of Fa and Its Variantsmentioning

confidence: 99%

Nature-Inspired Algorithms and Applied Optimization

Yang¹

2018

Studies in Computational Intelligence

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Optimal estimation of power system harmonics using a hybrid Firefly algorithm-based least square method

Cited by 19 publications

References 16 publications

Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

Double‐ended travelling‐wave fault location based on residual analysis using an adaptive EKF

Nature-Inspired Algorithms and Applied Optimization

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