Signal Processing-based Artificial Intelligence Approach for Power Quality Disturbance Identification

Sakib, Md. Sadman; Islam, Md. Rashidul; Tanim, S. M. Sazzadul Haque; Alam, Md. Shafiul; Shafiullah, Md; Ali, Amjad

doi:10.1109/icaeee54957.2022.9836389

Cited by 3 publications

(2 citation statements)

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“…Embarking on a meticulous dissection, power quality disturbance signals undergo a comprehensive analysis through a sophisticated five-level decomposition, leveraging the prowess of Daubechies 4 (db4) as the designated mother wavelet 69,70 . This intricate process involves the instantiation of daughter wavelets, aptly referred to as template functions, with their width defining the elusive scale.…”

Section: Dwt Based Identification Of Pq Disturbancesmentioning

confidence: 99%

Perception of power quality disturbances using Fourier, Short-Time Fourier, continuous and discrete wavelet transforms

Priyadarshini,

Bajaj,

Prokop

et al. 2024

Sci Rep

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Electric power utilities must ensure a consistent and undisturbed supply of power, with the voltage levels adhering to specified ranges. Any deviation from these supply specifications can lead to malfunctions in equipment. Monitoring the quality of supplied power is crucial to minimize the impact of fluctuations in voltage. Variations in voltage or current from their ideal values are referred to as "power quality (PQ) disturbances," highlighting the need for vigilant monitoring and management. Signal processing methods are widely used for power system applications which include understanding of voltage disturbance signals and used for retrieval of signal information from the signals Different signal processing methods are used for extracting information about a signal. The method of Fourier analysis involves application of Fourier transform giving frequency information. The method of Short-Time Fourier analysis involves application of Short-Time Fourier transform (STFT) giving time–frequency information. The method of continuous wavelet analysis involves application of Continuous Wavelet transform (CWT) giving signal information in terms of scale and time where frequency is inversely related to scale. The method of discrete wavelet analysis involves application of Discrete Wavelet transform (DWT) giving signal information in terms of approximations and details where approximations and details are low and high frequency representation of original signal. In this paper, an attempt is made to perceive power quality disturbances in MATLAB using Fourier, Short-Time Fourier, Continuous Wavelet and Discrete Wavelet Transforms. Proper understanding of the signals can be possible by transforming the signals into different domains. An emphasis on application of signal processing techniques can be laid for power quality studies. The paper compares the results of each transform using MATLAB-based visualizations. The discussion covers the advantages and disadvantages of each technique, providing valuable insights into the interpretation of power quality disturbances. As the paper delves into the complexities of each method, it takes the reader on a journey of signal processing complexities, culminating in a nuanced understanding of power quality disturbances and their representations across various domains. The outcomes of this research, elucidated through energy values, 3D plots, and comparative analyses, contribute to a comprehensive understanding of power quality disturbances. The findings not only traverse theoretical domains but also find practical utility in real-world scenarios.

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Section: Dwt Based Identification Of Pq Disturbancesmentioning

confidence: 99%

Perception of power quality disturbances using Fourier, Short-Time Fourier, continuous and discrete wavelet transforms

Priyadarshini,

Bajaj,

Prokop

et al. 2024

Sci Rep

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show abstract

“…This method has limitation for detection of the single-stage PQ events and PQ events of two stages. In [9], authors designed a hybrid algorithm using DWT and ST to detect and categorize the PQEs in real-time scenarios. This method is applicable for recognition of single-stage PQ events, and performance is degraded in the presence of noise.…”

Section: Introductionmentioning

confidence: 99%

Power Quality Detection and Categorization Algorithm Actuated by Multiple Signal Processing Techniques and Rule-Based Decision Tree

Singh¹,

Sharma²,

Garg³

et al. 2023

Sustainability

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This paper introduces a power quality (PQ) detection and categorization algorithm actuated by multiple signal processing techniques and rule-based decision tree (RBDT). This is aimed to recognize PQ events of simple nature and higher order multiplicity with less computational time using hybridization of the signal processing techniques. A voltage waveform with a PQ event (PQE) is processed using the Stockwell transform (ST) to compute the Stockwell PQ detection index (SPDI). The voltage waveform is also processed using the Hilbert transform (HT) to compute the Hilbert PQ detection index (HPDI). A voltage waveform is also decomposed using the Discrete Wavelet transform (DWT) to compute the classification feature index (CFI) [CFI1 to CFI4]. A combined PQ detection index (CPDI) is computed by multiplication of the SPDI, the HPDI and CFI1 to CFI4. Incidence of a PQE on a voltage signal is located with the help of a location PQ disturbance index (LPDI) which is computed by differentiating the CPDI with respect to time. CFI5, CFI6 and CFI7 are computed from the SPDI, the HPDI and the CPDI, respectively. Categorization of PQ events is performed using CFI1 to CFI7 by the rule-based decision tree (RBDT) with the help of simple decision rules. We conclude that the proposed algorithm is effective to identify the PQE with an accuracy of 98.58% in a noise-free environment and 97.62% in the presence of 20 dB SNR (signal-to-noise ratio) noise. Ten simple nature PQEs and eight combined PQ events (CPQEs) with multiplicity of two, three and four are effectively detected and categorized using the algorithm. The algorithm is also tested to detect a sag PQ event due to a line-to-ground (LG) fault incident on a practical distribution utility network. The performance of the investigated method is compared with a DWT-based technique in terms of accuracy of classification with and without noise, maximum computational time of PQ detection and multiplicity of PQE which can be effectively detected. A simulation is performed using the MATLAB software. MATLAB codes are used for modelling the PQE disturbances and the proposed algorithm using mathematical formulations.

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Ways to Reduce the Impact of Pulsations in Local Power Supply Robotic Systems

Skuhariev,

Svitak,

Yasko

2024

dndivsovt

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An analysis of the changes in the flow of pulsation transforming the energy-dynamic indicators of on-board power electronics systems has shown that there are several options for solving this problem. The article outlines the main options for the current problem of pulsation in the energy systems of autonomous electrical systems, such as UAVs, robotic complexes, and other systems. The effectiveness of changes in pulsation is examined, in addition to directly assessing the effectiveness of stagnation strategies and methods. Also in the statistics, the optimal technical solutions for specific operating minds were identified. The prospects and future directives have been predicted based on the proposals for further research in the sphere of changes in pulsation in local life systems. In the future, it is predicted and supported by the development of technology and innovation in this country. To sum up, we can say that the statistics have analyzed the changes in pulsation in robotic local power supply systems, which is one of the key directions in the field of electrical engineering and electronics. Increased attention to this problem is due to the need for assured stability, reliability and greater energy efficiency of electronic systems. Research in this area is aimed at developing more comprehensive methods and strategies for reducing noise and pulsation in electrical systems. Assessing the effectiveness of stagnant methods, promoting the development of new technologies and innovation, as well as developing promising directions in this field opens the way to creating more stable and adaptive living systems. Replacement of advanced electronic filters, voltage stabilizers, selection of new materials and components, integration of intelligent energy management systems and optimization of essential energy resources local power supply systems – the whole purpose is to directly conduct further investigations. The growing demand for stable and efficient electronic systems is driven by current research and the introduction of new technologies to change pulsation. Technological developments and scientific research in this area open up broad prospects for reducing the power supply and ensuring the stability of the functioning of modern electronic devices.

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Signal Processing-based Artificial Intelligence Approach for Power Quality Disturbance Identification

Cited by 3 publications

References 0 publications

Perception of power quality disturbances using Fourier, Short-Time Fourier, continuous and discrete wavelet transforms

Perception of power quality disturbances using Fourier, Short-Time Fourier, continuous and discrete wavelet transforms

Power Quality Detection and Categorization Algorithm Actuated by Multiple Signal Processing Techniques and Rule-Based Decision Tree

Ways to Reduce the Impact of Pulsations in Local Power Supply Robotic Systems

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