• 제목/요약/키워드: Power Quality Disturbances

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DWT-based Denoising and Power Quality Disturbance Detection

  • Ramzan, Muhammad;Choe, Sangho
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권5호
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    • pp.330-339
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    • 2015
  • Power quality (PQ) problems are becoming a big issue, since delicate complex electronic devices are widely used. We present a new denoising technique using discrete wavelet transform (DWT), where a modified correlation thresholding is used in order to reliably detect the PQ disturbances. We consider various PQ disturbances on the basis of IEEE-1159 standard over noisy environments, including voltage swell, voltage sag, transient, harmonics, interrupt, and their combinations. These event signals are decomposed using DWT for the detection of disturbances. We then evaluate the PQ disturbance detection ratio of the proposed denoising scheme over Gaussian noise channels. Simulation results also show that the proposed scheme has an improved signal-to-noise ratio (SNR) over existing scheme.

결정결합 방법을 이용한 전력외란 신호의 식별 (Power Quality Disturbance Classification using Decision Fusion)

  • 김기표;김병철;남상원
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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    • pp.915-918
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    • 2000
  • In this paper, we propose an efficient feature vector extraction and decision fusion methods for the automatic classification of power system disturbances. Here, FFT and WPT(wavelet packet transform) are und to extract an appropriate feature for classifying power quality disturbances with variable properties. In particular, the WPT can be utilized to develop an adaptable feature extraction algorithm using best basis selection. Furthermore. the extracted feature vectors are applied as input to the decision fusion system which combines the decisions of several classifiers having complementary performances, leading to improvement of the classification performance. Finally, the applicability of the proposed approach is demonstrated using some simulations results obtained by analyzing power quality disturbances data generated by using Matlab.

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Simplified Control Scheme of Unified Power Quality Conditioner based on Three-phase Three-level (NPC) inverter to Mitigate Current Source Harmonics and Compensate All Voltage Disturbances

  • Salim, Chennai;Toufik, Benchouia Mohamed
    • Journal of Electrical Engineering and Technology
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    • 제8권3호
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    • pp.544-558
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    • 2013
  • This paper proposes a simplified and efficient control scheme for Unified Power Quality Conditioner (UPQC) based on three-level (NPC) inverter capable to mitigate source current harmonics and compensate all voltage disturbances perturbations such us, voltage sags, swells, unbalances and harmonics. The UPQC is designed by the integration of series and shunt active filters (AFs) sharing a common dc bus capacitor. The dc voltage is maintained constant using proportional integral voltage controller. The shunt and series AF are designed using a three-phase three-level (NPC) inverter. The synchronous reference frame (SRF) theory is used to get the reference signals for shunt and the power reactive theory (PQ) for a series APFs. The reference signals for the shunt and series APF are derived from the control algorithm and sensed signals are injected in tow controllers to generate switching signals for series and shunt APFs. The performance of proposed UPQC system is evaluated in terms of power factor correction and mitigation of voltage, current harmonics and all voltage disturbances compensation in three-phase, three-wire power system using MATLAB-Simulink software and SimPowerSystem Toolbox. The simulation results demonstrate that the proposed UPQC system can improve the power quality at the common connection point of the non-linear load.

Determination of Power-Quality Disturbances Using Teager Energy Operator and Kalman Filter Algorithms

  • Cho, Soo-Hwan;Kim, Jeong-Uk;Chung, Il-Yop;Han, Jong-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제12권1호
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    • pp.42-46
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    • 2012
  • With the development of industry, more large-scale non-linear loads are added to existing power systems and they cause the serious power quality (PQ) problems to the nearby sensitive installations more and more. To protect the important loads and mitigate the impact of PQ disturbances on them, various compensating devices are installed. One of the most important control skills used in the compensating equipment at the load side is how fast they can recognize or detect the discontinuous abnormal PQ events from the normal voltage signal. This paper deals with two estimation methods for the fast detection and tracking of general PQ disturbances: Teager Energy Operator (TEO), which is a non-linear operator and used for a short time energy calculation, and Kalman Filter (KF), which is one of the most universally used estimation techniques. And it is also shown how to apply the TEO and the KF to detect the PQ disturbances such as voltage sag, swell, interruption, harmonics and voltage fluctuation.

전력 외란 자동 식별을 위한 특징 벡터 추출 기법 (A Feature Vector Extraction Method For the Automatic Classification of Power Quality Disturbances)

  • 이철호;이재상;조관영;정지현;남상원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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    • pp.404-406
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    • 1996
  • 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 FFT, DWT(Discrete Wavelet Transform), and data compression 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 7-class power quality disturbances generated by the EMTP are also provided.

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Complex Neural Classifiers for Power Quality Data Mining

  • Vidhya, S.;Kamaraj, V.
    • Journal of Electrical Engineering and Technology
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    • 제13권4호
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    • pp.1715-1723
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    • 2018
  • This work investigates the performance of fully complex- valued radial basis function network(FC-RBF) and complex extreme learning machine (CELM) based neural approaches for classification of power quality disturbances. This work engages the use of S-Transform to extract the features relating to single and combined power quality disturbances. The performance of the classifiers are compared with their real valued counterparts namely extreme learning machine(ELM) and support vector machine(SVM) in terms of convergence and classification ability. The results signify the suitability of complex valued classifiers for power quality disturbance classification.

Recognition and Classification of Power Quality Disturbances on the basis of Pattern Linguistic Values

  • Liu, XiaoSheng;Liu, Bo;Xu, DianGuo
    • Journal of Electrical Engineering and Technology
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    • 제11권2호
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    • pp.309-319
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    • 2016
  • This paper presents a new recognition and classification method for power quality (PQ) disturbances on the basis of pattern linguistic values. This method solves the difficulty of recognizing disturbances rapidly and accurately by using fuzzy logic. This method uses classification disturbance patterns to define the linguistic values of fuzzy input variables and used the input variables of corresponding disturbance pattern to set membership functions. This method also sets the fuzzy rules by analyzing the distribution regularities of the input variable values. One characteristic of this method is that the linguistic values of fuzzy input variables and the setting of membership functions are not only related to the input variables but also to the character of classification disturbance and the classification results. Furthermore, the number of fuzzy rules is equal to the number of disturbance patterns. By using this method for disturbance classification, the membership function and design of fuzzy rules are directly related to the objective of classification, thus effectively reducing the complexity of the design process and yielding accurate classification results. The classification results of the simulation and measured data verify the feasibility and effectiveness of this method.

Power Quality Improvement for Grid Connected Inverters under Distorted and Unbalanced Grids

  • Kim, Hyun-Sou;Kim, Jung-Su;Kim, Kyeong-Hwa
    • Journal of Power Electronics
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    • 제16권4호
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    • pp.1578-1586
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    • 2016
  • A power quality improvement scheme for grid connected inverters, even in the presence of the disturbances in grid voltages due to harmonic distortions and three-phase imbalance, is presented for distributed generation (DG) power systems. The control objective is to force the inverter currents to follow their references with robustness even under external disturbances in grid voltages. The proposed scheme is realized by a disturbance observer (DOB) based current control scheme. Since the uncertainty in a system can be effectively canceled out using an estimated disturbance by the DOB, the resultant system behaves like a closed-loop system consisting of a disturbance-free nominal model. For experimental verification, a 2 kVA laboratory prototype of a grid connected inverter has been built using a digital signal processor (DSP) TMS320F28335. Through comparative simulations and experimental results under grid disturbances such as harmonic distortion and imbalance, the effectiveness of the proposed DOB based current control scheme is demonstrated.

전력시스템 고조파 외란의 자동식별 (Automatic Classification of Power System Harmonic Disturbances)

  • 김병철;김현수;남상원
    • 제어로봇시스템학회논문지
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    • 제6권7호
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    • pp.551-558
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    • 2000
  • In this paper a systematic approach to automatic classificationi of power system harmonic disturbances is proposed where the proposed approach consists of the following three steps:(i) detecting and localizing each harmonic disturbance by applying discrete wavelet transform(DWT) (ii) extracting an efficient feature vector from each detected disturbance waveform by utilizing FFT and principal component analysis (PCA) along with Fisher's criterion and (iii) classifying the corresponding type of each harmonic disturbance by recognizing the pattern of each feature vector. To demonstrate the performance and applicability of the proposed classification procedure some simulation results obtained by analyzing 8-class power system harmonic disturbances being generated with Matlab power system blockset are also provided.

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웨이브렛 해석을 적용한 전력 품질 응용에 대한 장애의 유형에 관한 분석 (Wavelet analysis of distortion types for power quality applications)

  • 김상억;정영식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 A
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    • pp.145-147
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    • 2003
  • The wavelet transform has attracted considerable attention in the field of power quality analysis recently. This paper discuss the voltage sag and harmonic disturbances by using wavelet analysis. A discrete wavelet-based approach is applied for determining the characteristics of these disturbances.

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