567 research outputs found
An open-phase fault detection method for six-phase induction motor drives
Malaga (Spain), 4th to 6th April, 2017
Comunicaciones del Congreso Publicadas en: Renewable Energy and Power Quality Journal (RE&PQJ) ISSN 2172 038X, No.15 April 2017Induction machines (IM) with multiple sets
of three-phase windings are a real alternative in safety-
critical applications due to their inherent redundancy
and extra number of freedom degrees. These
properties
can be used to devel
op
a fault-tolerant system without
extra hardware. The fault detection is mandatory
in
the creation of a fault tolerant system. Since, the fault
localization allows to adapt the control scheme of this
anomalous mode of operation. Nowadays, open-phase
faults (OPFs) and six-phase IMs are hot topics in the
literature
of fault-tolerant drives. Thus, this paper
presents an open-phase fault detection method for
a
six-phase IM drive
. The detection method is based o
n
the vector space decomposition (VSD), taking the
components of the secondary orthogonal subspace to
localize the open-phase fault. The goodness of the
proposed method is validated with simulation resultsMinisterio de Ciencia e Innovacion ENE2014-52536-C2–1-
Robust strategy for fault location in electric distribution system
Power quality is a relevant aspect in power distribution systems, which considers service continuity and distortion of the current and voltage waveforms, among others; in the first, the fault location plays a fundamental role. Considering the requirement of reliable tools to improve the distribution system operation, this dissertation analyses, on the one hand, the confidence of two fault location approaches versus the waveform distortion and on the other hand, the adequate selection of its adjusting-variables when using learning-based fault locators (LBFL)
Hybrid approach for an optimal adjustement of a knowledge-based regression technique for locating faults in power distribution systems
This paper is focused in the development of a hybrid approach based on support vector machines (SVMs) which are used as a regression technique and also in the Chu-Beasley genetic algorithm (CBGA) which is used as an optimization technique to solve the problem of fault location. The proposed strategy consists of using the CBGA to adequately select the best configuration parameters of an SVM. As aresult of the application of this strategy, a well-suited tool is obtained to relate a set of inputs to a single output in a classical regression task,which is next used to determine the fault distance in power distribution systems, using single end measurements of voltage and current. Theproposed approach is initially tested in a simplified regression task using two functions in Â1 and Â2, where the results obtained are highlysatisfactory. Next, the selection of the adequate calibration parameters is performed in order to adjust the SVM using a cross validation strategy, where an average error of 5.75 % is obtained. These results show the adequate performance of the proposed methodology whichmerges SVM and CBGA into one powerful fault locator for application in power distribution systems
Accurate location of high impedance and temporary faults in radial distribution networks using distributed travelling wave observers
This thesis addresses a novel method for fault location in radial distribution networks and provides a new vision for the optimal deployment of synchronised voltage travelling wave (TW) observers in distribution networks. The proposed method can locate high impedance and temporary faults. The delay effect of transformers is demonstrated by theory and laboratory tests. A new method to eliminate the transformer’s effect on the accuracy of the fault location algorithm is presented
Conceptual mechanization studies for a horizon definition spacecraft communications and data handling subsystem
Conceptual mechanization for horizon definition spacecraft communications and data handling subsyste
Fault Location in Grid Connected Ungrounded PV Systems Using Wavelets
Solar photovoltaic (PV) power has become one of the major sources of renewable energy worldwide. This thesis develops a wavelet-based fault location method for ungrounded
PV farms based on pattern recognition of the high frequency transients due to switching
frequencies in the system and which does not need any separate devices for fault location.
The solar PV farm used for the simulation studies consists of a large number of PV modules connected to grid-connected inverters through ungrounded DC cables. Manufacturers
report that about 1% of installed PV panels fail annually. Detecting phase to ground faults in ungrounded underground DC cables is also difficult and time consuming. Therefore, identifying ground faults is a significant problem in ungrounded PV systems because such earth
faults do not provide sufficient fault currents for their detection and location during system operation. If such ground faults are not cleared quickly, a subsequent ground fault on the healthy phase will create a complete short-circuit in the system, which will cause a fire hazard and arc-flashing. Locating such faults with commonly used fault locators requires costly external high frequency signal generators, transducers, relays, and communication devices as well as generally longer lead times to find the fault.
This thesis work proposes a novel fault location scheme that overcomes the shortcomings of the currently available methods. In this research, high frequency noise patterns are used to identify the fault location in an ungrounded PV farm. This high frequency noise is generated due to the switching transients of converters combined with parasitic capacitance
of PV panels and cables. The pattern recognition approach, using discrete wavelet transform (DWT) multi-resolution analysis (MRA) and artificial neural networks (ANN), is utilized to
investigate the proposed method for ungrounded grid integrated PV systems.
Detailed time domain electromagnetic simulations of PV systems are done in a real-time
environment and the results are analyzed to verify the performance of the fault locator. The fault locator uses a wavelet transform-based digital signal processing technique, which uses the high frequency patterns of the mid-point voltage signal of the converters to analyze the ground fault location. The Daubechies 10 (db10) wavelet and scale 11 are chosen as the appropriate mother wavelet function and decomposition level according to the characteristics of the noise waveform to give the proposed method better performance. In this study, norm values of the measured waveform at different frequency bands give unique features at different fault locations and are used as the feature vectors for pattern recognition. Then, the three-layer feed-forward ANN classifier, which can automatically classify the fault locations according to the extracted features, is investigated. The neural network is trained with the Levenberg-Marquardt back-propagation learning algorithm.
The proposed fault locating scheme is tested and verified for different types of faults, such as ground and line-line faults at PV modules and cables of the ungrounded PV system. These faults are simulated in a real-time environment with a digital simulator and the data is then analyzed with wavelets in MATLAB. The test results show that the proposed method
achieves 99.177% and 97.851% of fault location accuracy for different faults in DC cables and PV modules, respectively. Finally, the effectiveness and feasibility of the designed fault
locator in real field applications is tested under varying fault impedance, power outputs, temperature, PV parasitic elements, and switching frequencies of the converters. The results demonstrate the proposed approach has very accurate and robust performance even with
noisy measurements and changes in operating conditions
Determining the locations of faults in distribution systems
The conventional approach for estimating the locations of transmission line faults has been to measure the apparent impedance from a line terminal to the fault and to convert the reactive component of the impedance to line length. Several methods, that use voltages and currents measured at one or both line terminals, have been proposed in the past. Methods for locating faults on radial transmission lines and rural distribution feeders have also been suggested. These methods do not adequately address the problems associated with fault location on distribution systems that have single or multiphase laterals and/or tapped loads. A technique that estimates the location of a shunt fault on a radial distribution system that has several single and/or multiphase laterals has been developed. Load taps and non-homogeneity of the system are taken into account. The apparent location of a fault is first estimated by computing the impedance from the fundamental frequency voltage and current phasors, and converting the reactive component of the impedance to line length. The sequence voltages and currents at the fault are expressed as functions of the distance to the fault as well as the impedances of loads beyond the fault. The expression for the imaginary component of the fault impedance is equated to zero and the resulting equation is solved using an iterative approach. Multiple estimates may be obtained for a fault in a distribution system that has laterals. One of the estimates is identified as the most likely fault location by using information from fault indicators which are strategically placed on the laterals. The developed technique, which can handle single-phase-to-ground, two-phase-to-ground, phase-to-phase and balanced three-phase faults was tested to evaluate its suitability. Results from computer simulations of faults indicate that the proposed technique is more accurate than the reactive component method. Studies also demonstrate that the sensitivity of the proposed technique is comparable to that of the reactive component method. A prototype fault location system was also developed. The system was tested using simulated voltage and current waveforms. Results show a close agreement with those obtained from the non-real time tests
Fault location in power distribution systems considering a dynamic load model
In the electrical power systems, load is one of the most difficult elements to be represented by an adequate mathematical model due to its complex composition and dynamic and non-deterministic behavior. Nowadays, static and dynamic load models have been developed for several studies such as voltage and transient stability, among others. However, on the issue of power quality, dynamic load models have not been taken into account in fault location. This paper presents a fault location technique based on sequence components, which considers static load models of constant impedance, constant current and constant power. Additionally, an exponential recovery dynamic load model, which is included in both the fault locator and the test system, is considered. This last model is included in order to consider the dynamic nature of the load and the performance of the fault locators under this situation. To demonstrate the adequate performance of the fault locator, tests on the IEEE 34 nodes test feeder are presented. According to the results, when the dynamic load model is considered in both the locator and the power system, performance is in an acceptable range.En los sistemas eléctricos de potencia, la carga es uno de los elementos matemáticamente más difíciles de representar debido a sucompleja composición y su comportamiento dinámico y no determinístico. Actualmente, se han desarrollado modelos estáticos y dinámicos de carga para diversos estudios, tales como estabilidad de tensión y estabilidad transitoria, entre otros. Sin embargo, en el campo de la calidad de la energía no se han tenido en cuenta los modelos dinámicos en la localización de fallas. Este artículo presenta una técnica de localización de fallas basada en componentes de secuencia, que considera modelos estáticos de impedancia constante, corriente constante y potencia constante. Además, se considera un modelo dinámico de recuperación exponencial, tanto en el localizador como en el sistema de pruebas. Este modelo se incluye para considerar la naturaleza dinámica de la carga y el desempeño de los localizadores ante esta situación. Para demostrar el desempeño adecuado del localizador de fallas, se realizaron pruebas en el sistema IEEE de 34 nodos. De acuerdo con los resultados, cuando se considera el modelo dinámico tanto en el localizador como en el sistema, el desempeño está en un rango aceptable
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