Islanding Detection Technique based on Karl Pearson’s Coefficient of Correlation for Distribution Network with High Penetration of Distributed Generations

Sareen, Karan; Bhalja, Bhavesh R.; Srivastava, Sanjay; Swarnkar, Yogendra; Maheshwari, R. P.

doi:10.1515/ijeeps-2017-0232

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…The results showed that, from the perspective of MILC, there may be certain differences in gene expression between dicotyledonous plants and monocotyledonous plants of chloroplast genomes. Karl Pearson’s correlation analysis between SCUO and MILC was used to explore the effect of CUB ( Sareen et al, 2018 ). Based on the gene expression level, we observed a significant positive between SCUO and MILC values ( P < 0.01; Table 4 ), indicating that the gene expression levels may be affected by the CUB.…”

Section: Discussionmentioning

confidence: 99%

Comparative Analysis of Codon Bias in the Chloroplast Genomes of Theaceae Species

et al. 2022

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Theaceae species are dicotyledonous angiosperms with extremely high ornamental and economic value. The chloroplast genome is traditionally used to study species evolution, expression of chloroplast genes and chloroplast transformation. Codon usage bias (CUB) analysis is beneficial for investigations of evolutionary relationships and can be used to improve gene expression efficiency in genetic transformation research. However, there are relatively few systematic studies of the CUB in the chloroplast genomes of Theaceae species. In this study, CUB and nucleotide compositions parameters were determined by the scripts written in the Perl language, CodonW 1.4.2, CU.Win2000, RStudio and SPSS 23.0. The chloroplast genome data of 40 Theaceae species were obtained to analyse the codon usage (CU) characteristics of the coding regions and the influence of the source of variation on CUB. To explore the relationship between the CUB and gene expression levels in these 40 Theaceae plastomes, the synonymous codon usage order (SCUO) and measure independent of length and composition (MILC) values were determined. Finally, phylogenetic analysis revealed the genetic evolutionary relationships among these Theaceae species. Our results showed that based on the chloroplast genomes of these 40 Theaceae species, the CUB was for codons containing A/T bases and those that ended with A/T bases. Moreover, there was great commonality in the CUB of the Theaceae species according to comparative analysis of relative synonymous codon usage (RSCU) and relative frequency of synonymous codon (RFSC): these species had 29 identical codons with bias (RSCU > 1), and there were 19 identical high-frequency codons. The CUB of Theaceae species is mainly affected by natural selection. The SCUO value of the 40 Theaceae species was 0.23 or 0.24, and the chloroplast gene expression level was moderate, according to MILC values. Additionally, we observed a positive correlation between the SCUO and MILC values, which indicated that CUB might affect gene expression. Furthermore, the phylogenetic analysis showed that the evolutionary relationships in these 40 Theaceae species were relatively conserved. A systematic study on the CUB and expression of Theaceae species provides further evidence for their evolution and phylogeny.

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Section: Discussionmentioning

confidence: 99%

Comparative Analysis of Codon Bias in the Chloroplast Genomes of Theaceae Species

et al. 2022

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“…To assess the reliability of the simulation of the nature and rate of change of the selected parameters, it is proposed to use one of the most common statistical methods for assessing the degree of similarity -correlation analysis, which makes it possible to determine the correlation between the change in the parameters of the power system in the case of disturbances in the ST and HRTSim. To quantify the correlation, the Pearson's correlation coefficient (r) is used [33], the absolute value of which ranges from 0 to 1. The closer r is to 1, the more similar the nature of the compared time series is.…”

Section: B Validation Criteriamentioning

confidence: 99%

Validation of Positive-Sequence Modeling of Large-Disturbance Stability in a Distribution Network With Distributed Generation Using the Hybrid Comprehensive Simulator

et al. 2021

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One of the general trends in power industry is the penetration of distributed generation (DG) units. The ongoing transformation of electric power systems (EPS) due to this penetration leads to a significant change in the properties of power systems. The problem arises in the ensuring stability of distribution system with DG units and EPS as a whole, especially in the case of large disturbances. The main way of solving this problem is positive-sequence phasor time-domain simulation. However, the known simplifications and limitations are inevitably applied at such simulation. In this regard, the obtained simulation results need to be validated. This paper proposes an alternative approach for validation of processes calculations, based on the use of a benchmark tool instead of field data. The hybrid simulator is proposed to use as a benchmark tool, because such simulator allow to obtain comprehensive information about a single spectrum of wave, electromagnetic, electromechanical processes in power system in cases of different large disturbances. That makes possible to identify the impact of the applied simplifications and limitations in the positive-sequence simulation on the reliability of power system stability assessment in the case of large disturbances. The studies presented in this paper were carried out using the scheme of distribution system with DG units, which is part of a real EPS. The obtained results demonstrate the arising errors in stability calculations, the nature of their changing and causes of occurrence, as well as factors affecting them.

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“…2101 loading condition and it is normalized [23]. ANN is trained with the selected features as input.…”

Section: Figure 1 Digital Filtering Technique Of Wavelet Transform (Wt)mentioning

confidence: 99%

Islanding detection in a distribution network with distributed generators using signal processing techniques

Kim

Ray

Salkuti

2020

IJPEDS

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This paper proposes quick & accurate islanding detection technique for a distribution system with distributed generators (DGs). Here two schemes of islanding detection based on signal processing is proposed of which one is based on discrete wavelet transform (DWT) with artificial neural network (ANN), and another one is based on S-transform with ANN. The negative sequence current/voltage signals are retrieved at targeted DG location which are used for islanding detection in the distribution system. Here, the wavelet and S-transforms are used for fault location and classification applications. Further, the feature extraction is used for reducing the size of data matrix by transforming it into set of features. In this work, particle swarm optimization (PSO) based feature selection scheme is applied. Simulation results on test system indicate the efficacy of proposed islanding detection techniques.

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Islanding Detection Technique based on Karl Pearson’s Coefficient of Correlation for Distribution Network with High Penetration of Distributed Generations

Cited by 4 publications

References 24 publications

Comparative Analysis of Codon Bias in the Chloroplast Genomes of Theaceae Species

Comparative Analysis of Codon Bias in the Chloroplast Genomes of Theaceae Species

Validation of Positive-Sequence Modeling of Large-Disturbance Stability in a Distribution Network With Distributed Generation Using the Hybrid Comprehensive Simulator

Islanding detection in a distribution network with distributed generators using signal processing techniques

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