Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders

This paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE.

PMUs optimized allocation using a tabu search algorithm for fault location in electric power distribution system

Phasor Measurement Units (PMUs) optimized allocation allows control, monitoring and accurate operation of electric power distribution systems, improving reliability and service quality. Good quality and considerable results are obtained for transmission systems using fault location techniques based on voltage measurements. Based on these techniques and performing PMUs optimized allocation it is possible to develop an electric power distribution system fault locator, which provides accurate results. The PMUs allocation problem presents combinatorial features related to devices number that can be allocated, and also probably places for allocation. Tabu search algorithm is the proposed technique to carry out PMUs allocation. This technique applied in a 141 buses real-life distribution urban feeder improved significantly the fault location results. © 2004 IEEE.

Fault location in underground systems through optimum-path forest

In this paper we propose an accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the Time Domains Reflectometry method for signal acquisition, which was further analyzed by OPF and several other well known pattern recognition techniques. The results indicated that OPF and Support Vector Machines outperformed Artificial Neural Networks classifier. However, OPF has been much more efficient than all classifiers for training, and the second one faster for classification. © 2011 IEEE.

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Improved Fault Location on Distribution Feeders Based on Matching During-Fault Voltage Sags

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fault location in underground systems using artificial neural networks and PSCAD/EMTDC

The need for high reliability and environmental concerns are making the underground networks the most appropriate choice of energy distribution. However, like any other system, underground distribution systems are not free of failures. In this context, this work presents an approach to study underground systems using computational tools by integrating the software PSCAD/EMTDC with artificial neural networks to assist fault location in power distribution systems. Targeted benefits include greater accuracy and reduced repair time. The results presented here shows the feasibility of the proposed approach. © 2012 IEEE.

Defects location in power systems components through a dedicated genetic algorithm

In this work the problem of defects location in power systems is formulated through a binary linear programming (BLP) model based on alarms historical database of control and protection devices from the system control center, sets theory of minimal coverage (AI) and protection philosophy adopted by the electric utility. In this model, circuit breaker operations are compared to their expected states in a strictly mathematical manner. For solving this BLP problem, which presents a great number of decision variables, a dedicated Genetic Algorithm (GA), is proposed. Control parameters of the GA, such as crossing over and mutation rates, population size, iterations number and population diversification, are calibrated in order to obtain efficiency and robustness. Results for a test system found in literature, are presented and discussed. © 2004 IEEE.

Location of single line-to-ground faults on distribution feeders using voltage measurements

This paper proposes a dedicated algorithm for lation of single line-to-ground faults in distribution systems. The proposed algorithm uses voltage and current phasors measured at the substation level, voltage magnitudes measured at some buses of the feeder, a database containing electrical, operational and topological parameters of the distribution networks, and fault simulation. Voltage measurements can be obtained using power quality devices already installed on the feeders or using voltage measurement devices dedicated for fault location. Using the proposed algorithm, likely faulted points that are located on feeder laterals geographically far from the actual faulted point are excluded from the results. Assessment of the algorithm efficiency was carried out using a 238 buses real-life distribution feeder. The results show that the proposed algorithm is robust for performing fast and efficient fault location for sustained single line-to-ground faults requiring less than 5% of the feeder buses to be covered by voltage measurement devices. © 2006 IEEE.

Fault analysis in four-wire distribution networks

The neutral wire in most existing power flow and fault analysis software is usually merged into phase wires using Kron's reduction method. In some applications, such as fault analysis, fault location, power quality studies, safety analysis, loss analysis etc., knowledge of the neutral wire and ground currents and voltages could be of particular interest. A general short-circuit analysis algorithm for three-phase four-wire distribution networks, based on the hybrid compensation method, is presented. In this novel use of the technique, the neutral wire and assumed ground conductor are explicitly represented. A generalised fault analysis method is applied to the distribution network for conditions with and without embedded generation. Results obtained from several case studies on medium- and low-voltage test networks with unbalanced loads, for isolated and multi-grounded neutral scenarios, are presented and discussed. Simulation results show the effects of neutrals and system grounding on the operation of the distribution feeders.

Steel bars identification in reinforced concrete structures by using ANN and magnetic fields

This work proposes a methodology for non destructive testing (NDT) of reinforced concrete structures, using superficial magnetic fields and artificial neural networks, in order to identify the size and position of steel bars, embedded into the concrete. For the purposes of this paper, magnetic induction curves were obtained by using a finite element program. Perceptron Multilayered (PML) ANNs, with Levemberg-Marquardt training algorithm were used. The results presented very good agreement with the expect ones, encouraging the development of real systems based upon the proposed methodology.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Modelo estocástico de programação matemática de alocação de medidores de tensão em alimentadores radiais de distribuição de energia elétrica para localização de faltas e monitoramento do perfil de tensão

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Proposta de Algoritmos Inteligentes para Localizar Faltas e Monitorar a Qualidade da Energia em Redes de Distribuição de Energia Elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Proposta de um algoritmo eficiente para a localização de faltas por relé diferencial numérico para proteção de linhas de transmissão com compensação série controlada por tiristores (TCSC)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Localizador de faltas por ondas viajantes em linhas de transmissão

It is important to ensure smoothly operation of a transmission line, sending energy to the consumption centers with minimal interruptions and safer. With this necessity, the fault location techniques have grown, in order to mitigate the impact of the fault and its correction can be more quickly and accurately. This paper presents a comparison between two different techniques of fault location, the fault location by impedance method, which uses the line parameters, the impedance per distance, voltage and current signals, and the other is the traveling wave method, which uses only a very fast analysis of time, synchronization and length between the line ends, do not using voltage and current values, but the temporal perception of the fault. Using travelling waves fault detection makes the previous knowledge of line parameters obsolete, which helps a lot network technicians and engineers with a quick and easy analysis. The methods are simulated in ATP Draw software, so both algorithms can be evaluated for their effectively and accuracy