• Title/Summary/Keyword: Power Quality Disturbances

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Improved Evaluation Method of Flicker considering Disturbances of Power System

  • Kim, Jae-Chul;Moon, Jong-Fil;Jung, Seung-Bock;Choe, Kyu-Ha
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.22 no.3
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    • pp.8-14
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    • 2008
  • This paper studies a more exact flicker evaluation method by detecting power quality disturbances and excluding the effects of power quality disturbances. Up to the present, power quality disturbances affect flicker evaluation index because power quality problems do not have been considered. However, flick index should represent only flicker without power quality disturbances. Thus, in this paper, we present the improved flicker evaluation method which removing the effects of power quality disturbances such as voltage sag and transient caused by fault and inverter/breaker switching. We detect voltage sag and transient using wavelet transform and remove the effects of power quality disturbances from flicker index.

Power Quality Disturbance Detection in Distribution Systems Using Wavelet Transform (웨이브렛 변환을 이용한 배전계통의 전력품질 외란 검출에 관한 연구)

  • Son Yeong-Rak;Lee Hwa-Seok;Mun Kyeong-Jun;Park June Ho;Yoon Jae-Young;Kim Jong-Yul;Kim Seul-Ki
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.54 no.7
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    • pp.328-336
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    • 2005
  • Power quality has become concern both utilities and their customers with wide spread use of electronic and power electronic equipment. The poor quality of electric power causes malfunctions, instabilities and shorter lifetime of the load. In power system operation, power system disturbances such as faults, overvoltage, capacitor switching transients, harmonic distortion and impulses affects power quality. For diagnosing power quality problem, the causes of the disturbances should be understood before appropriate actions can be taken. In this paper we present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances. This paper deals with the use of a multi-resolution analysis by a discrete wavelet transform to detect power system disturbances such as interruption, sag, swell, transients, etc. We also proposed do-noising and threshold technique to detect power system disturbances in a noisy environment. To find the better mother wavelet for detecting disturbances, we compared the performance of the disturbance detection with the several mother wavelets such as Daubechies, Symlets, Coiflets and Biorthogonals wavelets. In our analysis, we adopt db4 wavelet as mother wavelet because it shows better results for detecting several disturbances than other mother wavelets. To show the effectiveness of the proposed method, a various case studies are simulated for the example system which is constructed by using PSCAD/EMTDC. From the simulation results. proposed method detects time Points of the start and end time of the disturbances.

Power Quality Disturbances Detection Technique using Filter Bank and Adaptive Filters (필터뱅크와 적응필터를 이용한 전력품질 외란 검출기법)

  • Yun, Jae-Jun;Lee, Jeong-Kyu;Sohn, Sang-Wook;Bae, Hyeon-Deok
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.1
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    • pp.162-167
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    • 2012
  • In power quality monitoring, it is very important to detect disturbances (sag, swell, transient, and interruption) accurately. In this paper, a detection method for power quality disturbances by combining the filter bank system and adaptive filter is proposed. To decompose power signal, binary tree structured filter bank system is designed. In the filter bank system, the fundamental filter bank(QMF bank) is used as a module in each decomposing level. An adaptive filter is used to improve the detection accuracy of disturbances for each subband signal. In the adaptive filter, the measure of estimated error change is used to detect singular points of power quality disturbances. Computer simulations were performed on synthetic signals which have disturbances to assess the performance of the proposed method.

Automatic classification of power quality disturbances using orthogonal polynomial approximation and higher-order spectra (직교 다항식 근사법과 고차 통계를 이용한 전력 외란의 자동식별)

  • 이재상;이철호;남상원
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1436-1439
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    • 1997
  • The objective of this paper is to present an efficient and practical approach to the automatic classification of power quality(PQ) disturbances, where and orthogonal polynomial approximation method is emloyed for the detection and localization of PQ disturbances, and a feature vector, newly extracted form the bispectra of the detected signal, is utilized for the automatic rectgnition of the various types of PQ disturbances. To demonstrae the performance and applicabiliyt of the proposed approach, some simulation results are provided.

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Power Quality Disturbances Identification Method Based on Novel Hybrid Kernel Function

  • Zhao, Liquan;Gai, Meijiao
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.422-432
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    • 2019
  • A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

A Study on Filcker Evaluation Considering Power Quality Disturbance of Power System (전력계통의 전력품질 외란을 고려한 플리커 평가에 관한 연구)

  • Jung, Seung-Bock;Kim, Jae-Chul;Lee, Bong-Yi;Cho, Hyun-Kyung
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2005.05a
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    • pp.391-393
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    • 2005
  • This paper studies flicker evaluation considering power quality disturbance. A flicker problem with light device irritates human's eyes. Also, the flicker problem has an influence on adverse effect such as rolling device and rotating device. However, a study of flicker evaluation is not complete. A flicker is measured and evaluated at monitoring point. But we consider power quality disturbances such as voltage sag and transient that cause fault and inverter/breaker switching. Power quality disturbances affects flicker evaluation. A flicker evaluation index increases. Therefore, we consider power quality disturbances. We detect voltage sag and transient using wavelet and evaluate flicker without flicker index including power quality disturbances.

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A Study on Filcker Evaluation Considering Power Quality Disturbance of Power System (전력계통의 전력품질 외란을 고려한 플리커 평가에 관한 연구)

  • Jung, Seung-Bock;Kim, Jae-Chul
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2006.05a
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    • pp.376-379
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    • 2006
  • This paper studies flicker evaluation considering power quality disturbance. A flicker problem with light device irritates human's eyes. Also, the flicker problem has an influence on adverse effect such as rolling device and rotating device. However, a study of flicker evaluation is not complete. A flicker is measured and evaluated at monitoring point. But we consider power qualify disturbances such as voltage sag and transient that cause fault and inverter/breaker switching. Power quality disturbances affects flicker evaluation. A flicker evaluation index increases. Therefore, we consider power quality disturbances. We detect voltage sag and transient using wavelet and evaluate flicker without flicker index including power quality disturbances.

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Power Quality Disturbances Detection and Classification using Fast Fourier Transform and Deep Neural Network (고속 푸리에 변환 및 심층 신경망을 사용한 전력 품질 외란 감지 및 분류)

  • Senfeng Cen;Chang-Gyoon Lim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.115-126
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    • 2023
  • Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

Classification of Power Quality Disturbances Using Feature Vector Combination and Neural Networks (특징벡터 결합과 신경회로망을 이용한 전력외란 식별)

  • Nam, Sang-Won
    • Proceedings of the KIEE Conference
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    • 1997.11a
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    • pp.671-674
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    • 1997
  • The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FIT, DWT(Discrete Wavelet Transform), and Fisher's criterion are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 10-class power quality disturbances are also provided.

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An Improved PSO Algorithm for the Classification of Multiple Power Quality Disturbances

  • Zhao, Liquan;Long, Yan
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.116-126
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    • 2019
  • In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.