Дисертації з теми "Power quality disturbances"
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Parsons, Antony Cozart. "Automatic location of transient power quality disturbances /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
Повний текст джерелаDwijaya, Saputra I. "Detection of power disturbances for power quality monitoring using mathematical morphology." Thesis, University of Liverpool, 2017. http://livrepository.liverpool.ac.uk/3009798/.
Повний текст джерелаSettipalli, Praveen. "AUTOMATED CLASSIFICATION OF POWER QUALITY DISTURBANCES USING SIGNAL PROCESSING TECHNIQUES AND NEURAL NETWORKS." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_theses/430.
Повний текст джерелаAxelberg, Peter. "On Tracing Flicker Sources and Classification of Voltage Disturbances." Doctoral thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-3416.
Повний текст джерелаAndo, Junior Oswaldo Hideo. "Desenvolvimento de uma metodologia para identificar e quantificar distúrbios da qualidade da energia elétrica." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2009. http://hdl.handle.net/10183/18419.
Повний текст джерелаThis dissertation presents a methodology for detection and quantification of power quality disturbances. Digital signal processing (DSP) is applied to simulated and measured disturbances. The use of DSP enables the construction of digital filters for the detection of events, and the estimation of the frequency of voltage and current signals. The disturbances set by ANEEL and ONS standards are quantified by the proposed algorithm. The program developed was tested using simulated disturbance for its validation. Field measurements were used to assess the robustness of the algorithm against signal noise and other disturbances. This research presents effective and practical software that can be used to develop a new device for measuring the disturbances of Power Quality. The results obtained through the analysis of data (simulated and field measurements) validated the proposed algorithm.
Rosado, Sebastian Pedro. "Analysis of Electric Disturbances from the Static Frequency Converter of a Pumped Storage Station." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/34448.
Повний текст джерелаMaster of Science
Alshahrani, Saeed Sultan. "Detection, classification and control of power quality disturbances based on complementary ensemble empirical mode decomposition and artificial neural networks." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15872.
Повний текст джерелаMoses, Paul S. "Operation and performance of three-phase asymmetric multi-leg power transformers subjected to nonlinear and dynamic electromagnetic disturbances." Thesis, Curtin University, 2012. http://hdl.handle.net/20.500.11937/1529.
Повний текст джерелаAl, Abed Isrà. "Measurement System at Large Bandwidth for Quality Evaluation of Electric Energy up to 150 kHz." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
Знайти повний текст джерелаOubrahim, Zakarya. "On electric grid power quality monitoring using parametric signal processing techniques." Thesis, Brest, 2017. http://www.theses.fr/2017BRES0102/document.
Повний текст джерелаThis thesis deals with electric grid monitoring of power quality (PQ) disturbances using parametric signal processing techniques. The first contribution is devoted to the parametric spectral estimation approach for signal parameter extraction. The proposed approach exploits the multidimensional nature of the electrical signals.For spectral estimation, it uses an optimization algorithm to minimize the likelihood function. In particular, this algorithm allows to improve the estimation accuracy and has lower computational complexity than classical algorithms. An in-depth analysis of the proposed estimator has been performed. Specifically, the estimator performances are evaluated under noisy, harmonic, interharmonic, and off-nominal frequency environment. These performances are also compared with the requirements of the IEEE Standard C37.118.2011. The achieved results have shown that the proposed approach is an attractive choice for PQ measurement devices such as phasor measurement units (PMUs). The second contribution deals with the classification of power quality disturbances in three-phase power systems. Specifically, this approach focuses on voltage sag and swell signatures. The proposed classification approach is based on two main steps: 1) the signal pre-classification into one of 4 pre-classes and 2) the signature type classification using the estimate of the symmetrical components. The classifier performances have been evaluated for different data length, signal to noise ratio, interharmonic, and total harmonic distortion. The proposed estimator and classifier are validated using real power system data obtained from the DOE/EPRI National Database of Power System Events. The achieved simulations and experimental results clearly illustrate the effectiveness of the proposed techniques for PQ monitoring purpose
Carvalho, Flavio Gomes de. "Caracterização do conteúdo harmônico em ambientes residenciais: estudo de caso." Universidade Federal da Paraíba, 2015. http://tede.biblioteca.ufpb.br:8080/handle/tede/7556.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
In this work a characterization of harmonic content in residential electrical systems through a set of measurements over various periods of time is performed. For each reported case it was a statement of charges that make up the installation and an individual analysis of each of them as a way to assess their influence on the harmonic behavior of the installation as a whole.
Neste trabalho é realizada uma caracterização do conteúdo harmônico em instalações elétricas residenciais por meio de um conjunto de medições realizadas por diversos períodos de tempo. Para cada caso avaliado fez-se um levantamento das cargas que compõem a instalação e uma análise individual de cada uma delas como forma de avaliar sua influência no comportamento harmônico da instalação como um todo.
Arruda, Elcio Franklin de. "Análise de distúrbios relacionados com a qualidade da energia elétrica utilizando a transformada Wavelet." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-25102007-090916/.
Повний текст джерелаThe aim of the present dissertation is to apply the Wavelet transform to analyze power quality problems, detecting, localizing and classifying them. The topic Wavelet transform, has appeared in the literature as a new tool for the analysis of signals, using functions called mother Wavelet to map signals in its domain, supplying information in the time and frequency domain, simultaneously. Wavelet transform is accomplished through filters decomposing a provided signal in multiresolution analysis. The detection and localization of disturbances are obtained by decomposing a signal into two other signals that represent, a detailed version (high frequency signals) and a smoothed version (low frequency signals). The smoothed version is decomposed again, and new detailed and smoothed signals are obtained. This process is repeated as many times as necessary and the disturbances can be detected and localized in the time as a function of its level frequency. This information also supplies characteristics to each disturbance, allowing classifying them. Thus, this research presents a way to develop an automatic classifying algorithm of power quality disturbances, based only on multiresolution analysis.
Arruda, Bruno Willian de Souza. "Classificação de distúrbios de energia elétrica baseada em sistemas imunológicos artificiais." Universidade Federal da Paraíba, 2015. http://tede.biblioteca.ufpb.br:8080/handle/tede/7557.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
Nowadays, electricity assumes an essential role in the sustainability of modern society. The requirement and consumer demand for power quality are growing along with the advancement of technology and the increasing use of non-linear loads. This paper presents an application of artificial immune systems, focusing on the clonal selection algorithm, for power quality disturbances classification. The algorithm uses an initial population of antibodies to generate high affinity memory cells capable of recognizing antigenic electrical disturbances during each half cycle of the fundamental frequency voltage signal. The results demonstrate the algorithm's ability to classify disturbances such as sag, swell, outage and harmonics, with 100% efficiency rating. Another important feature of this approach is that it can be embedded, since the online stage classification has a low computational complexity with processing time around 103 μs. Based on comparative study with other studies, the results showed up best.
Na atualidade, a energia elétrica assume um papel imprescindível para a sustentabilidade da sociedade moderna. Com o avanço da tecnologia e a utilização cada vez maior de cargas não-lineares, são crescentes a exigência e a demanda dos consumidores em relação à qualidade de energia elétrica. Neste trabalho é apresentada uma aplicação de sistemas imunológicos artificiais, tendo como foco o algoritmo de seleção clonal, para classificação de distúrbios de energia elétrica. O algoritmo utiliza uma população inicial de anticorpos para gerar células de memória de alta afinidade antigênica capazes de reconhecer distúrbios de energia elétrica a cada meio ciclo da frequência fundamental do sinal de tensão. Os resultados obtidos demonstram a capacidade do algoritmo em classificar distúrbios, tais como afundamentos, elevações, interrupções e harmônicos, com 100% de eficiência de classificação. Outra característica importante desta abordagem é que ela pode ser embarcada, uma vez que a fase online de classificação apresenta baixa complexidade computacional com tempo de processamento em torno de 103 μs. Baseado no estudo comparativo com outros trabalhos, os resultados obtidos apresentaram-se melhores.
Phan, Anh Tuan. "Power Systems Model Developments for Power Qality Monitoring : Application to Fundamental Frequency and Unbalance Estimation." Thesis, Mulhouse, 2016. http://www.theses.fr/2016MULH8692/document.
Повний текст джерелаRenewable energy, electricity and smart grids are core subjects as they have great environmental and societal impacts. Thus, generating, transporting and managing electric energy, i.e., power, still continue to drive a growing interest. In order to properly achieve these goals, several locks must be removed. Beyond issues related to the distribution architecture, the formalization of models, sizing tools, features and indicators, constraints and criteria, decentralized generation and energy management, power quality is central for the whole grid’s reliability. Disturbances affect the power quality and can cause serious impact on other equipment connected to the grid. The work of this thesis is part of this context and focuses on the development of models, indicators, and signal processing methods for power quality monitoring in time-varying power distribution systems.This thesis analyzes the power quality including several well-known features and their relevance. Power system models and signal processing methods for estimating their parameters are investigated for the purpose of real-time monitoring, diagnostic and control tasks under various operating conditions. Among all, the fundamental frequency is one of the most important parameters of a power distribution system. Indeed, its value which is supposed to be a constant varies continuously and reflects the dynamic availability of electric power. The fundamental frequency can also be affected by renewable energy generation and by nasty synchronization of some devices. Moreover, the power absorbed by loads or produced by sources is generally different from one phase to the other one. Obviously, most of the existing residential and industrial electrical installations with several phases work under unbalanced conditions. Identifying the symmetrical components is therefore an efficient way to quantify the imbalance between the phases of a grid. New state-space representations of power systems are proposed for estimating the fundamental frequency and for identifying the voltage symmetrical components of unbalanced three-phase power systems. A first state-space representation is developed by supposing the fundamental frequency to be known or to be calculated by another estimator. In return, it provides other parameters and characteristics from the power system. Another original state-space model is introduced which does not require the fundamental frequency. Here, one state variable is a function of the frequency which can thus be deduced. Furthermore this new state-space model is perfectly are able to represent a three-phase power system in both balanced and unbalanced conditions. This not the case of lots of existing models. The advantage of the proposed state-space representation is that it gives directly access to physical parameters of the system, like the frequency and the amplitude and phase values of the voltage symmetrical components. Power systems parameters can thus be estimated in real-time by using the new state-space with an online estimation process like an Extended Kalman Filter (EKF). The digital implementation of the proposed methods presents small computational requirement, elegant recursive properties, and optimal estimations with Gaussian error statistics.The methods have been implemented and validated through various tests respecting real technical constraints and operating conditions. The methods can be integrated in active power filtering schemes or load-frequency control strategies to monitor power systems and to compensate for electrical disturbances
Carlsson, Fredrik. "On impacts and ride-through of voltage sags exposing line-operated AC-machines and metal processes." Doctoral thesis, KTH, Electrical Systems, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3681.
Повний текст джерелаDuring the last decade, power quality has been recognised asa global problem. Among different types of power qualityproblems, voltage sags have been identified to be one of themost severe problems for different process industries. The mostcommon reason to voltage sags is lightning strikes in powerlines. Protection equipment, usually located at switchyards,disconnect faulted power lines as soon as possible, which isapproximately 100 ms. Thus, the duration of voltage sags areapproximately 100 ms. The sensitivity to voltage sags ofelectrical equipment in process industries can be observed asfor instance malfunction, automatic turnoff or damages.
This thesis gives an overview of three metals processes withfocus on the sensitivity to voltage sags and interruptions. Theinherent energy in the process is used to find the sensitivity.This energy may also be used to obtain "ride-through" for theprocesses. The three metals processes are a blast furnaceprocess, a hot rolling mill process and a cold rolling millprocess. The main attention in this thesis is paid to the blastfurnace process, which is powered by a line-operatedsynchronous machine.
The thesis shows that the protection equipment forelectrical machines can be adjusted to avoid unnecessaryshutdowns. It is also explained why there are high torque andcurrents during voltage sags as well as after voltage sags. Itis shown that the first peak torque and current during thevoltage sags is almost proportional to the voltage change, thatis the voltage magnitude before the voltage sag minus thevoltage magnitude during the voltage sag. The first peak torqueand current after the voltage sag depends sinusoidal-like onthe duration of the voltage sag and almost proportional to thevoltage change during the voltage sag. There is no fluxsaturation during voltage sags, however after voltage sagssaturation is very likely to occur. The thesis explains why andalso how the flux is changed during and after voltage sags.
The duration of voltage sags is in many cases set by theprotection equipment located in switchyards. It is shown thatthe durations of voltage sags can be changed to durations thatwill cause less peak torque and current after voltage sags forline-operated AC-machines. It is also shown how this istheoretically achieved.
Keywords:Rolling mill, Blast furnace, Power Quality,Synchronous machine, Asynchronous machine, Voltage sag, Voltageinterruption, Ride-through, Process disturbances, Simulation,Modelling
Cândido, Marcos Rogério. "Aplicação da transformada Wavelet na análise da qualidade de energia em fornos elétricos a arco." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/3/3143/tde-09022009-181024/.
Повний текст джерелаA new method for the detection and classification of the disturbances that affect the electric power quality in industrial electric systems with electric arc furnaces was developed in this work. During the fusion process of the electric arc furnaces, may occur several events that affect the electric system to which it is inserted may occur, having as characteristic: waveform of the signal of current highly unbalanced and with great distortion due to the harmonic, scintillation effects; as well as sag and swell in the voltage signals.The method proposed was applied to real signals, allowing the detection and classification of the multiple disturbances in the waveform of the voltage signal originating from the operation of the electric arc furnace. For this purpose, a technique based on Wavelet Transform will be used and applied to the not-stationary signals of an industrial installation with three electric arc furnaces.
Borges, Fábbio Anderson Silva. "Extração de características combinadas com árvore de decisão para detecção e classificação dos distúrbios de qualidade da energia elétrica." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-01102013-104201/.
Повний текст джерелаThis work presents a methodology for detection and classification of disturbance related to the electric power quality. The detection is performed using only one rule to infer in the presence or not of the disturbance in a window analyzed. For the classification is proposed a method based on decision tree. The tree receives as input features of the extracted signal both in time domain and in the frequency domain, being the last obtained by Fourier transform. It is emphasized that all the features extraction methodology was idealized as an attempt to reduce to the maximum the computational effort for the tasks of detection and classification of disturbances. In short, it is possible to verify that the results obtained are satisfactory for the purpose of this research.
Borges, Fábbio Anderson Silva. "Método híbrido baseado no algoritmo k-means e regras de decisão para localização das fontes de variações de tensões de curta duração no contexto de Smart Grid." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-04102017-105849/.
Повний текст джерелаIn the Smart Grids context, the correct location of short-duration voltage variations sources is not a trivial task, because of the short duration of these events and for rapid propagation in the distribution feeder. In this sense, aiming to develop a recursive hybrid method based on machine learning area tools (clustering algorithm and rule base) that is able to locate the sources of short-duration voltage variations, it was used data from smart meters installed along the distribution feeder. The recursive hybrid method, as input, received the disturbance characteristics provided by the meters installed in the system. Thus, this thesis aimed to development of a measurement hardware for signal acquisition, detection, classification through a realtime operating system. Then, k-means clustering algorithm grouped the meters data in order to define two clusters, where one of them corresponded to the meters that were distant from the region that occurred the disturbance and the other one corresponded to the meters, which were located near to the disturbance occurrence region. In a second step, a rule-based system determined which of the clusters corresponded to the source node. When the algorithm determined a very large region, that region was recursively introduced as input of the developed methodology to decrease its size. The resulting system was able to estimate the location region with a accuracy above 90%. Therefore, this method showed a suitable design for employment by operation control centers of power sector concessionaires, aiming to support technical staff decision to stablish assertive corrective actions.
Souza, Silvio Aparecido de. "Utilização da Transformada de Fourier Janelada para caracterização de distúrbios na qualidade da energia elétrica." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-12052017-104820/.
Повний текст джерелаThis dissertation presents a study of Windowed Fourier Transform applied to Power Quality. By the implementation of a computational algorithm, this approach aims to detect, locate and classify disturbances that may occur in Power Systems. Variations in voltage waveforms, such as sag, swell, interruption, oscillatory transient and noise have became frequent in electric systems, attracting the attention to the power quality supplied. The analysis of such phenomena, which is usually described either in the time domain (differential equation resolution) or in the frequency domain (Fourier Transform), can now be analyzed simultaneously in both domains: time and frequency, by the windowed Fourier Transform. The windows used to provide this information are the Hanning, rectangular and Kaiser. The simulation of the diverse disturbances occurred in the distribution system was accomplished by means of ATP software - Alternative Transients Program - whose characteristics correctly follow a real distribution system of CPFL electric utility. The tests show the windowed Fourier Transform has a great potentiality when applied to evaluate the power quality.
Santos, Crisluci Karina Souza. "Classifica??o de dist?rbios na rede el?trica usando redes neurais e wavelets." Universidade Federal do Rio Grande do Norte, 2008. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15119.
Повний текст джерелаCoordena??o de Aperfei?oamento de Pessoal de N?vel Superior
Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbance s occurrences in the network. This work presents a methodology based on the Discrete Wavelet Transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks
An?lises p?s-despacho de sinais oriundos de registradores de perturba??es fornecem muitas vezes informa??es importantes para identifica??o e classifica??o de dist?rbios nos sistemas, visando a uma gest?o mais eficiente do fornecimento de energia el?trica. Para auxiliar nessa tarefa, faz-se necess?rio recorrer a t?cnicas de processamento de sinais, a fim de automatizar o diagn?stico sobre os tipos de dist?rbio presentes nos sinais registrados. A transformada wavelet constitui-se em uma ferramenta matem?tica bastante eficaz na an?lise de sinais de tens?o ou corrente, obtidos imediatamente ap?s a ocorr?ncia de dist?rbios na rede. Este trabalho apresenta uma metodologia baseada na transformada wavelet discreta e na compara??o de curvas de distribui??o da energia de sinais, com e sem dist?rbio, para diferentes n?veis de resolu??o de sua decomposi??o, com o objetivo de obter descritores que permitam a sua classifica??o atrav?s do uso de redes neurais artificiais
Filho, Odilon Delmont. "Um algoritmo para detecção, localização e classificação de distúrbios na qualidade da energia elétrica utilizando a transformada wavelet." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/18/18154/tde-15062007-074110/.
Повний текст джерелаA perfect power supply would be one that is always available, maintaining the supply voltage and frequency within certain limits, and supplying pure noise free sinusoidal waveform. Nevertheless, transient events are usual in power systems, resulting in several interferences. The purpose of this study is for detecting, locating in time and to classifying with wavelet transform (WT) several disturbances that occur on power systems. A WT theoretical revision, referring to the first mention in wavelet up to the recent research advances is presented. Only WT was used in order to detect and locate in time the power system disturbances. For classification, three mathematical tools were compared: WT, FFT (Fast Fourier Transform) and ANN (Artificial Neural Networks). A distribution System, with identical characteristics as the real distribution system, was performed with ATP software (Alternative Transients Program). The results showed that multiresolution analysis technique is able to detect and locate all the generated and analyzed voltage disturbances. For classification the results were similar for the WT, FFT and ANN, however FFT and ANN results presented a better performance. The results conclude that the WT algorithm is efficient at detecting, localizing and classifying power system disturbances, as well as, at estimating the amplitude and duration of the voltage disturbance.
Filho, Odilon Delmont. "Utilização da transformada Wavelet para caracterização de distúrbios na qualidade da energia elétrica." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-14012005-153030/.
Повний текст джерелаThis dissertation presents a study of Wavelet transform applied to power quality in order to detect, locate and classify disturbances that may occur in the power system. Initially an introduction of power quality is presented, showing facts, evolutions and explaining the concept of the main phenomena that interfere the on power quality of the brazilian power system, due to, mainly, a great demand for electronic devices produced nowadays. A revision of the main methods and models currently applied in the world regarding this subject is also show. The Wavelet transform comes as a great support in the area of signal assessment, as it can extract information about time and frequency simultaneously, differently from the Fourier transform. The simulation of the diverse disturbances occurred in the system was accomplished through ATP software (Alternative Transients Program), whose characteristics correctly follow a system of real distribution of CPFL eletric utility. The generated and analyzed voltage disturbances were detected and located by Multiresolution Analysis technique and later classified by the method of the Standard Deviation
Lin, Zhemin. "The economic losses of power quality disturbance : different perspectives of cost models." Thesis, University of Strathclyde, 2012. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=18700.
Повний текст джерелаAndrade, Luciano Carli Moreira de. "Transformada Wavelet e técnicas de inteligência computacional aplicadas à identificação, compressão e armazenamento de sinais no contexto de qualidade da energia elétrica." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/18/18154/tde-09082017-081609/.
Повний текст джерелаThe presence of disturbances in the electrical power supplied to consumers can decrease the lifetime of the equipment, cause malfunction or even their breakdown. Thus, tools able to perform detection, localization, classification, compression and storage of signals automatically and organized manner are essential to ensure adequate monitoring process to electric power systems as a whole. Among the tools commonly applied to the tasks mentioned above, one can highlight the Wavelet Transform (WT) and Artificial Neural Networks (ANN). However, the WT has not been established yet and nor its level of decomposition, as well as the most appropriate ANN architecture and topology to the tasks already mentioned. The main fact that has led to this finding is due to the review of related literature, where it is possible to note the use of distinct WT and ANN. Therefore, the first contribution of this research was the design and development of an efficient method of segmentation of signals associate to Power Quality (PQ) disturbances. The developed method take advantage of WT properties of temporal identification of signal discontinuities. The second contribution is the development of an automatic algorithm that, through the segmentation method developed and classification by ANN, indicates the best tools (Wavelets and ANN) for the tasks of segmentation, extraction of characteristics and classification of QEE disturbances. This algorithm was developed based on the resources of the Evolutionary Algorithms and it adopts Multi-layered Perceptron type ANN, once this architecture can be considered consecrated with regard to the pattenrs classification. Finally, the third contribution is related to the development of EA based procedures in order to improve data compression methods that preserve the relevant information in the PQ signals. Thus, it is important to mention that the results of this research may determine automatic mechanisms to be used in the process of recording, processing and storing information that will be important in order to maintain an up-to-date (historical) database in the utilities, from which , indexes and a better mapping and understanding of all PQ related disturbances can be better understood and solved.
Сиченко, Віктор Григорович, Виктор Григорьевич Сыченко, Victor G. Sichenko та Viktor H. Sychenko. "Розвиток наукових основ підвищення електромагнітної сумісності підсистем електричної тяги постійного струму залізничного транспорту". Thesis, Видавництво Дніпропетровського національного університету залізничного транспорту імені академіка В. Лазаряна, 2011. http://eadnurt.diit.edu.ua/jspui/handle/123456789/816.
Повний текст джерелаUA: АНОТАЦІЯ Дисертаційну роботу присвячено вирішенню науково-технічної проблеми – підвищенню електромагнітної сумісності підсистем електричної тяги постійного струму в умовах впровадження швидкісного руху, що покращить техніко- економічні показники перевізного процесу, його енергоефективність та безпеку. В результаті еспериментальних досліджень розроблено математичні моделі завад, що дозволить точніше проектувати та моделювати пристрої енергетичних каналів тягового електропостачання постійного струму. Отримала подальший розвиток методологія активної фільтрації, що призводить до підвищення електромагнітної сумісності підсистем електричної тяги постійного струму як з суміжними пристроями залізничної інфраструктури, так і з лініями зовнішнього електропостачання при зменшенні габаритних розмірів та встановленої потужності застосовуваного обладнання. Очікуваний економічний ефект від впровадження запропонованих рішень перевищує 4 млн. грн. Отримані наукові результати дозволяють надати рекомендації щодо проектування нових енергоефективних електромагнітносумісних перетворювачів комбінованої ідеології для модернізації тягових підстанцій та силових активних фільтрів на підстанціях з застарілим обладнанням. RU: АННОТАЦИЯ Диссертационная работа посвящена решению актуальной научно- технической проблемы - повышению электромагнитной совместимости подсистем электрической тяги постоянного тока в условиях внедрения скоростного движения, которое улучшит технико-экономические показатели перевозочного процесса, его энергоэффективность и безопасность. Рассматривая ЭМС, как один из показателей качества функционирования системы тягового электроснабжения, необходимо охватывать весь комплекс технических средств, которые задействованы в процессе передачи и потребления электроэнергии и учитывать, что система тягового электроснабжения представляет собой сложную электродинамическую распределенную систему, которая характеризуется стохастическим характером изменения параметров функционирования. Эти параметры изменяются в пространстве, плоскости и времени, изменяя электромагнитную обстановку в комплексе система тягового электроснабжения-смежные устройства (линии внешнего энергоснабжения, автоблокировки и продольного электроснабжения, линии связи, информационные каналы передачи данных, каналы телеуправления и телесигнализации, рельсовые цепи). Основой этого влияния является распространение кондуктивних помех через разнообразные гальванические связи. В результате еспериментальних исследований установлено, что питающие напряжения 110 кВ и 35 кВ превышают предельно допустимые значения. Уровень напряжения на шинах 10 кВ, от которых питаются тяговые трансформаторы, также превышает номинальное значение, но на уровне, в основном, нормально допустимого значения отклонения. Несимметрия напряжения, как на шинах 110 кВ, так и на шинах 35-10 кВ, находится в допустимых пределах. Качество электроэнергии за показателем искажения синусоидальности напряжения на шинах 10 кВ тяговых подстанций с 6-пульсовыми выпрямителями не отвечает требованиям стандарта. Коефициент несимметрии напряжения по обратной последовательности в линиях автоблокировки (АБ) значительно более высокий (более чем в 3 раза) в сравнении с линиями продольного электроснабжения (ПЭ), что побуждает ставить вопрос необходимости симетрирования напряжений в линиях АБ. Коэффициент искажения синусоидальности напряжения в линии АБ на тяговой подстанции с 12- пульсовой схемой выпрямления значительно превышает предельно допустимое значение и почти вдвое выше за KU в линии ПЭ. При этом KU и на тяговой подстанции с 6-пульсовой схемой выпрямления выше по сравнению с линией ПЭ. То есть, существующая идеология питания линии АБ с применением двойной трансформации, выполняя задание ограничения токов короткого замыкания и гальванической развязки, в сущности резко ухудшает качество электрической энергии, которая формирует условия ухудшения электромагнитной совместимости. Исследованиями также установлено, что изменение нагрузки тяговой подстанции практически не осуществляет влияния на показатели качества электрической энергии системы внешнего электроснабжения. Режимы напряжения как в системе тягового электроснабжения, так и в системе внешнего электроснабжения определяются случайными факторами и имеют слабую статистическую связь между собой. Разработанные математические модели помех, позволят точнее проектировать и моделировать устройства энергетических каналов тягового электроснабжения постоянного тока. Отмечается, что энергетические каналы (ЭК) тягового электроснабжения должны обеспечивать надежность и бесперебойность питания, стойкость к непредсказуемым влияниям и высокую энергоэффективность. На современном этапе, кроме указанного, они должны быть электромагнитносовместимыми с окружающей средой на всех уровнях передачи, превращения и потребления электрической энергии. Указанные процессы обеспечиваются рядом разнообразных устройств, образовывающих, собственно, ЭК: линии электропередачи, трансформаторы, преобразователи, инфраструктура тяговой сети и потребители электрической энергии. Рассматриваются направления усовершенствования ЭК и возможные варианты их схемной реализации. Перспективными являются структуры децентрализованого питания и разработка систем питания с промежуточным звеном повышенной частоты. Основными устройствами энергетических каналов системы тягового электроснабжения являются тяговые преобразователи. Современный выпрямитель является сложным, многофункциональным устройством и выполняется на принципах комбинированной идеологии с расширенными функциями, в том числе осуществление функции активной фильтрации. В работе получила дальнейшее развитие методология активной фильтрации, которая приводит к повышению электромагнитной совместимости подсистем электрической тяги постоянного тока как со смежными устройствами железнодорожной инфраструктуры, так и с линиями внешнего электроснабжения при уменьшении габаритных размеров и установленной мощности применяемого оборудования. Ожидаемый экономический эффект от внедрения предложенных решений превышает 4 млн. грн. Полученные научные результаты позволяют предоставить рекомендации для проектирования новых энергоэффективных электромагнитносовместимых преобразователей комбинированной идеологии для модернизации тяговых подстанций и силовых активных фильтров на подстанциях с устаревшим оборудованием. EN: THE SUMMARY Thesis is dedicated to solve scientific and technical problems - improve electromagnetic compatibility of alternative current electric traction subsystems in a highspeed lines that will make possible to improve technical and economic characteristics of transportation process, its efficiency and security. On the basis of experimental studies the author developed mathematical models of disturbances, that will make possible to design and simulate devices of power traction DC supply systems in a more accurate way. The author developed the methodology of active filter, that leads to improve the electromagnetic compatibility of electric DC traction subsystems with adjoining devices of railway infrastructure and with external power supply systems reducing the overall dimensions and installed capacity of the applicable equipment. Expected economic effect of proposed approach exceeded 4 million grn. Proposed results can provide propositions about designing of new energy converters on the basis of combined ideology for modernization of traction substations and power active filters of substations with aging equipment.
Looja, Tuladhar R. "Control of Custom Power System using Active Disturbance Rejection Control." Cleveland State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=csu1438913443.
Повний текст джерелаManmek, Thip Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithm." Awarded by:University of New South Wales. Electrical Engineering and Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/26233.
Повний текст джерелаAguiar, Eduardo Pestana de. "Sistema de inferência Fuzzy para classificação de distúrbios em sinais elétricos." Universidade Federal de Juiz de Fora (UFJF), 2011. https://repositorio.ufjf.br/jspui/handle/ufjf/4149.
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A presente dissertação tem como objetivo discutir o uso de técnicas de otimização baseadas no gradiente conjugado e de informações de segunda ordem para o treinamento de sistemas de inferência fuzzy singleton e non-singleton. Além disso, as soluções computacionais derivadas são aplicadas aos problemas de classificação de distúrbios múltiplos e isolados em sinais elétricos. Os resultados computacionais, obtidos a partir de dados sintéticos de distúrbios em sinais de tensão, indicam que os sistemas de inferência fuzzy singleton e non-singleton treinados pelos algoritmos de otimização considerados apresentam maior velocidade de convergência e melhores taxas de classificação quando comparados com aqueles treinados pelo algoritmo de otimização baseada em informações de primeira ordem e é bastante competitivo em relação à rede neural artificial perceptron multicamadas - multilayer perceptron (MLP) e ao classificador de Bayes.
This master dissertation aims to discuss the use of optimization techniques based on the conjugated gradient and on second order information for the training of singleton or non-singleton fuzzy inference systems. In addition, the computacional solutions obtained are applied to isolated a multiple disturbances classification problems in electric signals. Computational results obtained from synthetic data from disturbances in electric signals indicate that singleton or non-singleton fuzzy inference systems trained by the considered optimization algorithms present greater convergence speed and better classification rates when compared to those data trained by an optimization algorithm based on first order information and is quite competitive with multilayer perceptron neural network and Bayesian classifier.
Oliveira, José Mário Menescal de. "Efeitos da operação do gerador de indução no comportamento do gerador síncrono operando em um sistema isolado alimentando cargas não lineares." Universidade Federal de Goiás, 2018. http://repositorio.bc.ufg.br/tede/handle/tede/8878.
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This thesis demonstrates the effects of harmonic pollution in a salient pole synchronous generator and an induction generator operating in parallel on an isolated system, supplying a non-linear load. The main contributions of this research-study consist of identifying and quantifying the oscillations that non-linear load cause on the electric variables of synchronous and induction generators, such as, the electromagnetic conjugate that presents oscillations of sixth harmonic due to the distorted currents.
Este trabalho mostra os efeitos da poluição harmônica em um gerador síncrono de polos salientes e um gerador de indução operando em paralelo em um sistema isolado suprindo carga não linear. As principais contribuições deste trabalho consistem em identificar e quantificar as oscilações que a carga não linear utilizada provoca nas variáveis elétricas dos geradores síncronos e dos geradores de indução, tal como, o conjugado eletromagnético que apresenta oscilações de sexto harmônico devido as correntes distorcidas.
Lima, Marcelo Antonio Alves. "Uma nova metodologia para análise da qualidade da energia elétrica sob condições de ocorrência de múltiplos distúrbios." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18154/tde-14112013-102931/.
Повний текст джерелаThe power system is susceptible to the presence of several sources of disturbances that harm the power quality. In this sense, its voltages and/or currents may contain multiple disturbances with simultaneous occurrence. This work presents a methodology that decomposes the measured signal in components which estimate the waveforms of the individual disturbances followed by their recognition when a multiple disturbance situation occurs. The Independent Component Analysis (ICA) is the main tool in the disturbance decomposition stage. The ICA is originally a technique applied in multivariate data analysis, which means that it requires measurements from multiple sensors allocated in different positions of the system. However, this work proposes its application for a single measured signal available. For this, two methods were developed in order to provide the required diversity to the ICA technique. It is demonstrated that both methods are equivalent to an adaptive linear filter bank capable to perform an unsupervised separation of multiple independent disturbances, if they are spectrally disjoint. A classification system based on artificial neural networks is proposed to identify the disturbances decomposed by the previous stage. The complete system is tested using synthetic and actual data, presenting highly satisfactory results for the decomposition of signals containing multiple disturbances, and precision for the classification task above 97%
BHAGAT, NEERAJ KUMAR. "DETECTIONOF POWER QUALITY DISTURBANCES." Thesis, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18945.
Повний текст джерелаKumar, Raj. "Assessment and mitigation of power quality disturbances." Thesis, 2016. http://localhost:8080/xmlui/handle/12345678/7153.
Повний текст джерелаHoang, TA. "Wavelet-based techniques for classification of power quality disturbances." Thesis, 2003. https://eprints.utas.edu.au/20549/1/whole_HoangTuanAnh2003_thesis.pdf.
Повний текст джерелаChoudhury, Debasis. "Characterization of Power Quality Disturbances using Signal Processing and Soft Computing Techniques." Thesis, 2013. http://ethesis.nitrkl.ac.in/4745/1/210EE2101.pdf.
Повний текст джерелаLu, Chen-Wen, and 呂振文. "A Study of Power Quality Disturbances-Monitoring Instrumentation and Measurement Technology." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/83298149758117506585.
Повний текст джерела國立成功大學
電機工程學系碩博士班
92
Electrical power signal measurement and analysis are two important aspects in power quality. In this dissertation, an application of virtual instrument approach for probing the data of power quality disturbances is first proposed. In the proposed instrumentation system, a data acquisition interface is implemented along with digital algorithms developed by LabVIEW tools. The proposed system can be applied to investigate different disturbances that include voltage harmonics, voltage flickers and three-phase voltage unbalances. Through a certain period of disturbance monitoring and recording, the trend-of-variation and the related statistical information of disturbances would be examined and analyzed. Results of simulated and actual data help confirm the feasibility of the method. As for measurement techniques, a continuous wavelet transform-based approach is proposed to assist the measurement of voltage flickering. A wavelet-direct demodulation (WDD) method is derived that is also compared with the fast Fourier transform covering frequency-domain direct demodulation (FDD) and indirect demodulation (IDD) methods, where the computation performances of each method were presently assessed based on the flicker-frequency response and system frequency deviation. Besides, to validate the practicality of the proposed method, the utility data measured near the arc furnace were also evaluated to support the method. Furthermore, by embodying the B-spline wavelet function, this dissertation also investigate the detection of the notch and spike signals. In addition to localizing the start and end point of the notch and spike signals, the proposed method also grasped the depth, width and area parameters of the encountered signals. Test results further solidify the proposed method in good agreement. Finally, as for the analysis of measured data, the estimation of the stochastic flicker characteristics for an electric arc furnace over a complete heat is examined thoroughly in this dissertation. These characteristics include stationarity, normality and correlation. Meanwhile, several fundamental statistical features were assessed at a different sampling periods. Test results for a typical AC arc furnace indicate that (1) most flicker characteristics are stationary or weakly stationary during different periods of a heat cycle, but most of their probability density functions are not normally distributed, (2) the voltage and current fluctuations in the same phase are highly correlated, (3) the flicker converges at a value with a ±5% deviations from the value based on a basic sampling period, if the sampling period is decreased below 12 seconds.
Behera, Satyajit, and Sudhanshu Sekhar Send. "Characterization of Various Power Quality Disturbances Based on Signal Processing and Artificial Intelligence Scheme." Thesis, 2015. http://ethesis.nitrkl.ac.in/7638/1/200.pdf.
Повний текст джерелаIanniello, Giacomo. "Power quality measurement methods aimed at disturbances detection and instrumentation susceptibility assessment." Tesi di dottorato, 2013. http://www.fedoa.unina.it/9380/1/Ianniello_Giacomo_25.pdf.
Повний текст джерелаKuan, Yu-ching, and 關羽慶. "Classification of Power Quality Disturbances Using Dynamic Time Warping and Particle Swarm Optimization." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/86315406144823615319.
Повний текст джерела國立雲林科技大學
電機工程系碩士班
93
Power system confronts power quality disturbances that are hard to avoid. Before assembling a protective device or finding a way of improvement, first the disturbance types need to be identified. Then, we can know what disturbances belong and why power system hitches. And we can get better power quality. This paper presents two approaches based on dynamic time warping and particle swarm optimization for classification of power quality disturbances. The first approach is based on heuristic rules and dynamic time warping for classification of power quality disturbances. In the classification process, the Walsh transform and fast Fourier transform are first used to get feature parameters for the input signals. Then, the vector quantization is used to speed up the dynamic time warping operation. Moreover, in order to reduce the dynamic time warping computational cost and increase the classification accuracy, the heuristic rules are introduced. Finally the effectiveness of the proposed approach is demonstrated by disturbance classification. The second approach is based on particle swarm optimization for classification of power quality disturbances. The test signal and reference pattern are matched with particle swarm optimization. It is changed that the characteristics of particle swarm optimization for get better results. It is concluded from the results that the method is very effective for classification power quality disturbances.
Chen, Cheng-I., and 陳正一. "Evaluation and Improvement of Signal Processing Techniques for Measurement of Power Quality Disturbances." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/74719997168502201637.
Повний текст джерела國立中正大學
電機工程所
97
With the widespread use of nonlinear loads in the power system, the power quality disturbances are increasingly present. These disturbances may introduce operational problems of power system equipments. Therefore, improving the power quality has become a great concern for both utilities and their customers. The frequency-domain methods have been widely used for the signal processing because of its computational efficiency. In addition, most power meters adopt the FFT-based algorithms to analyze the power signals. However, the FFT-based algorithms are less accurate if the system frequency varies and the frequency resolution decreases. The analytic results will show errors caused by the leakage and picket-fence effects. Therefore, many conventional analysis algorithms are necessary to improve for the detection of time-varying signals. For accurately and efficiently monitoring the power quality disturbances, such as harmonics, interharmonics, voltage flickers, sags, swells, and interruptions, this dissertation proposes several remedial strategies to improve the drawbacks of the commonly used signal processing algorithms in the literature. Besides, this dissertation applies LabVIEW and the dedicated hardware to design a simple virtual instrument and an educational platform for conveniently measuring power quality signals and the engineering education. The performance of improved algorithms is validated by testing the synthesized and actual signals.
Rentala, D. B., and M. Das. "A Novel method to Detect and Evaluate Power Quality disturbances using Hilbert Phase Shifting and CORDIC Algorithm." Thesis, 2014. http://ethesis.nitrkl.ac.in/5520/1/110EE0645-11.pdf.
Повний текст джерелаSwain, Sudarshan. "Grid Synchronization Control Schemes for a Three Phase Grid connected Photovoltaic System with Power Quality Disturbances." Thesis, 2019. http://ethesis.nitrkl.ac.in/10052/1/2019_PhD-SSudarshan_514EE1010_Grid.pdf.
Повний текст джерелаKuan, Chien-Hsun, and 管建勛. "Feature Selection for Identification and Classification of Power Quality Disturbances Based on Particle Glowworm Swarm Optimization (PGSO) Algorithm." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/38aw24.
Повний текст джерела中原大學
電機工程研究所
103
This study proposes an optimization feature selection scheme, which combines a glowworm swarm optimization (GSO) algorithm with a particle swarm optimization (PSO), namely particle glowworm swarm optimization (PGSO). The proposed PGSO-based scheme optimizes the smoothing parameters of LOOCV of probabilistic neural network (PNN). The least influenced features, rarely degrading the cross-validation accuracy, are removed from the candidate features by using the optimal smoothing parameters to reconstruct the optimal feature vectors set. This paper illustrates time-frequency and time-time relationships of 13 types of power quality disturbance (PQD) by using S-transform (ST) and TT-transform (TT) in the conditions of no noise, SNR=30dB, SNR=25dB, SNR=20dB and SNR=15dB. By observing the ST and TT contours, 6 types of time characteristic curves and 5 types of frequency characteristic curves are depicted. According to the time-frequency and the time-time relationships, 62 candidate features are calculated. The results show that the classification accuracies and runtimes of classifiers by using to the back propagation neural network (BPNN) is superior to that by using the optimal feature vectors set obtained by the proposed PGSO-based scheme, even in the environment with various noise interference.
Ringrose, MJ. "Studies of power quality : disturbance recognition." Thesis, 2003. https://eprints.utas.edu.au/11455/1/Ringrose_whole_thesis.pdf.
Повний текст джерелаPanda, Swastik Sovan. "Power Quality Disturbance Detection and Classification." Thesis, 2016. http://ethesis.nitrkl.ac.in/8274/1/2016_BT_112EE0247_Power_Quality.pdf.
Повний текст джерелаWang, Jen-Shuan, and 王仁舜. "Design the Chip for Classifying Power Quality Disturbance." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/13696311961748313383.
Повний текст джерела淡江大學
電機工程學系
92
Power quality (PQ) is recognized as an essential feature of a successful electric power system mainly due to the rapid increase of loads which generate noise and, at the same time, are sensitive to the noise present in the supply system. Existing techniques for recognizing and identifying power quality disturbance waveforms are primarily based on visual inspection of the waveform. It is the purpose of this study to bring to bear a recent advance method based on the artificial neural network to the problem of automatic power quality disturbance waveform classification. This study proposes a new approach to classify various types of power quality disturbance events based on a hierarchical artificial neural network and presents its implements on a field programmable gate array (FPGA). This proposed hierarchical neural network utilizes self-organizing feature map (SOM) networks and learning vector quantization (LVQ) networks. In the proposed network, the SOM networks provide an approximate method for computing the input vectors in an unsupervised manner with the approximation being specified by the synaptic weight vector of the neurons in the SOM. The computation of the SOM may therefore be viewed as the first stage of the proposed hierarchical network for solving the PQ classification problem. The second stage is provided by the LVQ networks. The LVQ network is based on a supervised learning techniques that uses class information to improve the quality of the classifies from the first stage. The multistages hierarchical classifier attempts to factorize the overall input vector into a number of small groups, each of which requires very little computation. Therefore, by use of the hierarchical classifier, the loss in accuracy can be small. The solution algorithm based on the proposed hierarchical network is then implemented by FPGA. This work presents the actual design of a system on a programmable chip (SOPC), and describes the related synthesis, layout, and verification phases. Finally, the effectiveness of the proposed algorithm and its hardware implementation is verified through various test experiments.
Yao-Hui, Nien, and 粘遙輝. "Power Quality Disturbance Waveform Recognition Using Neural Network." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/74303057801787422778.
Повний текст джерела淡江大學
電機工程學系
90
In recent years, because of rapid development of the high-tech industries, the limits on the specification higher power quality is strict. However, to improve the power quality, the import thing is to collect the information regarding to power quality events for analysis their properties. Therefore, enhancing the power quality analysis technique is one of the most important tasks in the power industry. This thesis utilized the import neural network technique to implement a PQ disturbance classifier. The PQ disturbance classifier is based on the Learning Vector Quantization algorithm implemented by Matlab. The classifier can classify the transient signals into voltage interruption, swell, sag, flicker, and harmonic. Users can characterize those power quality problems by this tool. To verify the performance of the proposed approach, this approach has been tested on many disturbance signals generated by MATLAB/SIMULINK. The accuracy and efficiency of the proposed approach are verified by many cases. The results show the propose approaches can identify the PQ disturbance correctly.
Sarkar, S. "Power quality disturbance detection and classification using signal processing and soft computing techniques." Thesis, 2014. http://ethesis.nitrkl.ac.in/6149/1/E-66.pdf.
Повний текст джерелаChen, Shih-Wei, та 陳世偉. "Power Quality Disturbance Recognition using Hidden Markov Models and SOFM Network withK-Means Algorithm". Thesis, 2007. http://ndltd.ncl.edu.tw/handle/75364705610335374653.
Повний текст джерела國立雲林科技大學
電機工程系碩士班
95
Because of widespread use of the sensitive electronic products, the requirements of power quality will be further emphasized. In order to know the reasons of occurrence for power quality disturbances, we need to get the signals of voltage/current disturbances that can be used to recognize what kind of disturbance event happen. Therefore, identification and recognition of voltage and current disturbances in power system is an important task in power system monitoring. This paper presents two approaches based on hidden Markov models and SOFM network withK-Means for recognition of power quality disturbances. The first presents an approach based on hidden Markov models for recognition of power quality disturbances. The feature extraction and vector quantization of disturbance signals are first made. Then, the hidden Markov models for each disturbance event are constructed. Finally, the test signals can be recognized by a forward algorithm and backward algorithm to obtain the results. Some discussions which include the characteristics of hidden Markov models and vector quantization are made to obtain better results. The second presents an approach based on SOFM network withK-Means algorithm for recognition of power quality disturbances. The feature extraction of disturbance signals are first made. Then, the SOFM network withK-Means algorithm for all disturbance data are trained to obtain map. Finally, the test signals can be recognized with map by SOFM network to obtain the results. Some discussions which include the characteristics of SOFM network withK-Means algorithm and enter noise disturbances are made to obtain better results.
Paracha, Zahir Javed. "Design and development of intelligent computational techniques for power quality data monitoring and management." Thesis, 2011. https://vuir.vu.edu.au/19381/.
Повний текст джерела