Extended vector fitting for subharmonics, harmonics, interharmonics, and supraharmonics estimation in electrical systems

Bañuelos-Cabral, E.S.; Gutierrez-Robles, José Alberto; Nuño-Ayón, J.J.; Sotelo-Castañón, J.; Naredo, J.L.

doi:10.1016/j.epsr.2023.109664

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…Since then, the concept of supraharmonics has gradually been accepted by the industry, and the harm caused by supraharmonics has become well-known. With the deepening of research, more scholars have now given a specific definition of supraharmonics [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Supraharmonic Detection Algorithm Based on Interpolation of Self-Convolutional Window All-Phase Compressive Sampling Matching Pursuit

Ji,

Yan,

Wang

2024

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With the increase in the use of high-frequency power electronic devices, the harmonics injected into the power grid show a trend of high-frequency development. The continuous rise of the supraharmonic emission level in the distribution network has become one of the power quality problems that needs to be solved urgently in the power grid. In this paper, an algorithm based on the Interpolation of the Self-convolutional Window All-phase Compressive Sampling Matching Pursuit (ISWApCoSaMP) is proposed. Firstly, the self-convolution operation is used for the maximum sidelobe decay (MSD) window, and then the compressed sampling matching pursuit model based on the All-phase is constructed, leading to the All-phase Compressive Sampling Matching Pursuit (ApCoSaMP). Finally, the four-spectrum-line interpolation is combined to utilize spectrum line information to improve the accuracy of signal parameter detection in the frequency domain. The introduced All-phase greatly improves the phase measurement accuracy because the initial phase of the supraharmonic signal is selected for phase estimation. In addition, the self-convolutional window and four-spectrum-line interpolation make full use of the information in the time and frequency domains, thus optimizing the measurement results of amplitude and frequency. The algorithm achieves high accuracy in the measurement results of simulated signals and accurately measures supraharmonics.

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Section: Introductionmentioning

confidence: 99%

Supraharmonic Detection Algorithm Based on Interpolation of Self-Convolutional Window All-Phase Compressive Sampling Matching Pursuit

Ji,

Yan,

Wang

2024

Information

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“…Leakage occurs when the data window used for the technique FFT does not contain a precise interval of integers of frequency cycles. Because this method depends on the information windows of the signal under monitoring, due to the inevitable changes in the signal frequency, the problem of leakage will therefore always exist in this method [15].…”

Section: Introductionmentioning

confidence: 99%

New Technology and Method for Monitoring the Status of Power Systems to Improve Power Quality—A Case Study

Ildarabadi

Zadehbagheri

2023

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The identification and analysis of harmonics, frequency, and transient events are essential today. It is necessary to have available data relating to harmonics, frequency, and transient events to understand power systems and their proper control and analysis. Power quality monitoring is the first step in identifying power quality disturbances and reducing them and, as a result, improving the performance of the power system. In this paper, while presenting different methods for measuring these quantities, we have made some corrections to them. These reforms have been obtained through the analysis of power network signals. Finally, we introduce a new monitoring system capable of measuring harmonics, frequency, and transient events in the network. In addition, these values are provided for online and offline calculations of harmonics, frequency, and transient events. In this paper, two new and practical methods of the “algebraic method” are used to calculate network harmonics and wavelet transform to calculate transient modes in the network. Furthermore, the proposed monitoring system is able to reduce the amount of data-storage memory. The results of the simulations performed in this article show the superiority of using the new method presented for online and offline monitoring of power quality in electric power systems.

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Astrophysics-based transit search optimization heuristics for parameter estimation of multi-frequency sinusoidal signals

Malik,

Chang,

Chaudhary

et al. 2024

Mod. Phys. Lett. B

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This study investigates an astrophysics-based Transit search optimization algorithm (TSOA) for solving a challenging engineering problem. This innovative strategy uses the fundamentals of physics to improve the accuracy and efficacy of problem solving techniques. Harmonic distortions in power systems have become a massive challenge because of the nonlinear loads associated with the electrical power distribution system. Overheating of the equipment, motor failure, capacitor failure, and improper power metering are all issues caused by harmonic distortion. A new examination of the causes and consequences of these issues, as well as the status of hardware and software available for harmonic evaluation, is necessary in light of the unprecedented advancements in power electronic devices and their integration at all levels in the power and energy system. In order to estimate phase and amplitude simultaneously with a specified frequency, an objective function of power system harmonics is created. Keeping in mind the adverse effects of harmonics, parameter estimation is carried out under various conditions by taking different particle sizes and signal-to-noise ratios. TSOA proved its efficacy for both phase and amplitude parameters under different situations and precisely estimated the harmonics signal up to an accuracy of 1.1648E–15. Two harmonic signals were taken in this research work, and the best MSE values achieved are 9.748E–4, 8.287E–07, 6.157E–10, and 1.165E–15 for 30, 60, 90, and 150 dB noise, respectively, under case study 1 while varying the particle size from 50 to 450. The results for case study 2 proved to be best up to 7.373E–16, and no significant change occurred by increasing the generations above 500. The proposed study would be a step further in developing a more accurate and robust computing platform for robust estimation of harmonics arising in power and energy systems.

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Extended vector fitting for subharmonics, harmonics, interharmonics, and supraharmonics estimation in electrical systems

Cited by 3 publications

References 11 publications

Supraharmonic Detection Algorithm Based on Interpolation of Self-Convolutional Window All-Phase Compressive Sampling Matching Pursuit

Supraharmonic Detection Algorithm Based on Interpolation of Self-Convolutional Window All-Phase Compressive Sampling Matching Pursuit

New Technology and Method for Monitoring the Status of Power Systems to Improve Power Quality—A Case Study

Astrophysics-based transit search optimization heuristics for parameter estimation of multi-frequency sinusoidal signals

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