K-nearest neighbor and naïve Bayes based diagnostic analytic of harmonic source identification

Jopri, Mohd Hatta; Ghani, Mohd Ruddin Ab; Abdullah, Abdul Rahim; Manap, Mustafa; Sutikno, Tole; Too, Jingwei

doi:10.11591/eei.v9i6.2685

Cited by 10 publications

(5 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Basic machine learning models that are used to identify harmonic sources have relatively low recognition accuracy. Reference [25] introduces two methods based on support vector machine (SVM) and naive Bayes (NB) classifiers to classify the voltage and current characteristics observed on different PCCs. When the simulation testing system is small, SVM shows better performance.…”

Section: Discussionmentioning

confidence: 99%

Composite Harmonic Source Detection with Multi-Label Approach Using Advanced Fusion Method

Sun,

Wang,

et al. 2024

Electronics

View full text Add to dashboard Cite

With the integration of clean energy and new power electronic devices into the power grid, the superposition of harmonic sources has become increasingly apparent and common. There is an urgent need to effectively identify composite harmonic sources in the new energy grid. This article proposes a multi-label composite harmonic source classification method that integrates knowledge representation with the transformer model. First, triplets from harmonic monitoring data are extracted and TransR models are used to train time-frequency feature representation vectors. Then, the transformer model is trained to learn the data features of different harmonic sources. Finally, based on the multi-label classification method, composite harmonic sources are identified. This article integrates the semantic information of time-frequency features into the data samples, increasing the interpretability of the model while expanding the inter-class features, which is conducive to the classification and recognition of the model. Compared with other deep learning recognition methods, verification based on simulation data and measured data shows that this method has low training complexity and higher recognition accuracy.

show abstract

Section: Discussionmentioning

confidence: 99%

Composite Harmonic Source Detection with Multi-Label Approach Using Advanced Fusion Method

Sun,

Wang,

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…The S-transform (ST) is hybrid of wavelet transform (WT) and the STFT, which inherits the advantages of both in signal processing [74], [75]. In the transformation process, ST uses a moving and scalable localising Gaussian window in particular.…”

Section: S-transformmentioning

confidence: 99%

Identification of harmonic source location in power distribution network

Jopri

Skamyin

Manap

et al. 2022

IJPEDS

Self Cite

View full text Add to dashboard Cite

This paper presents the experimental set-up of identification of harmonic source location in the power distribution network using time-frequency analysis, known as S-transform (ST) at the point of common coupling (PCC). S-transform offers high frequency resolution in analyzing the low frequency component and able to represent signal parameters in time-frequency representation (TFR) such as TFR impedance (ZTFR). The proposed method is based on IEEE Std. 1459-2010, ST, and the significant relationship of spectral impedances components (ZS) that been extracted from the ZTFR, consist of the fundamental impedance (Z1) and harmonic impedance (Zh). This experiment was conducted out on an IEEE 4-bus test feeder with a harmonic producing load in numerous different scenarios. The experimental was tested and verified for three consecutive months. The findings of this study reveal that the proposed method provides 100 percent correct identification of harmonic source location.

show abstract

“…In a number of papers, it is proposed to determine the parameters of inverters and rectifiers based on various methods, such as time-frequency analysis technique [33,34], periodogram technique [35,36], and machine learning algorithm [37,38]. Basically, such an analysis is carried out for the classification and localization of nonlinear loads [39,40].…”

Section: Introductionmentioning

confidence: 99%

Computation of Nonlinear Load Harmonic Currents in the Presence of External Distortions

et al. 2022

View full text Add to dashboard Cite

This paper deals with the issues of computation of the nonlinear load harmonic currents in the presence of external distortions based on the real measurements with help of passive harmonic. Such values are necessary when modeling an equivalent nonlinear load as current sources in the presence of external distortions. The passive filter allows to separate external and internal distortions, which is necessary when determining the harmonic currents of a single consumer. The influence of various parameters on the computation of harmonic currents of a nonlinear load, such as the parameters of a passive harmonic filter, the impedance of the power supply transformer, the load parameters of the consumer, taking into account the harmonic generation from the grid side, and from the consumer side, is considered. It is shown that an external source of distortion has practically no effect on the error in estimating the harmonic current magnitudes of a nonlinear load. The obtained simulation results were confirmed experimentally on a laboratory test bench. Recommendations for the selection of passive harmonic filter parameters have been developed to minimize the error in determining the harmonic current magnitudes of a nonlinear load.

show abstract

K-nearest neighbor and naïve Bayes based diagnostic analytic of harmonic source identification

Cited by 10 publications

References 41 publications

Composite Harmonic Source Detection with Multi-Label Approach Using Advanced Fusion Method

Composite Harmonic Source Detection with Multi-Label Approach Using Advanced Fusion Method

Identification of harmonic source location in power distribution network

Computation of Nonlinear Load Harmonic Currents in the Presence of External Distortions

Contact Info

Product

Resources

About