Rapid method for evaluating the margin of voltage stability due to Hopf bifurcation

Apesar do crescente desenvolvimento das metodologias de detecção de bifurcações de Hopf em sistemas de energia elétrica nas últimas décadas, alguns aspectos ainda carecem de progressos, especialmente frente à crescente necessidade de aumento da segurança na operação dos sistemas eletroenergéticos. Um destes aspectos diz respeito ao tempo de processamento destas metodologias para serem utilizadas em tempo real na operação do sistema. Este tempo computacional é pouco considerado para este fim pelas metodologias atualmente existentes. Assim sendo, o presente trabalho apresenta um novo desenvolvimento relativo a estimação da margem de estabilidade do sistema de potência referente à bifurcação de Hopf e considera o tempo computacional envolvido neste processo a fim de incluir a margem devido a Hopf na operação em tempo real do sistema. O desenvolvimento apresentado estende uma das metodologias que compõe o estado da arte através da flexibilização de um dos parâmetros de interesse em relação a margem de estabilidade devido a bifurcação de Hopf, a saber, a frequência do autovalor no ponto de birfurcação. Esta metodologia utiliza o método de Newton em um conjunto de equações, e neste trabalho ainda é proposta a utilização de um tratamento da esparsidade para este conjunto de equações, deixando o algoritmo mais rápido. De forma a apresentar a eficiência desta metodologia proposta, esta foi testada em dois sistemas, o sistema Kundur de duas áreas e o sistema IEEE 39 barras. Os resultados obtidos são comparados frente a resultados obtidos também para a metodologia clássica utilizada em centros de operação. Através destes resultados é possível mostrar a possibilidade de sua utilização em tempo real e elucidar as grandes melhorias obtidas através do desenvolvimento proposto.Despite the increasing development of Hopf bifurcations detection methods for electric power systems in the last decades, some aspects still require to progress, especially with the increasing necessity for higher safety in the electrical energy systems operation. One of these aspects concerns to the processing time of these methodologies to be used in real-time system operation. The computational time is disregarded for this purpose by the methods currently available. Therefore, this paper presents a new development for the power system stability margin estimation due to Hopf bifurcation and considers the computational time involved in this process to include the margin due to Hopf in electrical energy real-time operation. The presented development extends a methodology that makes up the state-of-the-art through an interest parameter relaxation in the stability margin due to Hopf bifurcation, namely, the eigenvalue frequency at the bifurcation point. This method uses Newton\'s method on a set of equations, and this work also proposes the use of a sparsity treatment for this set of equations, speeding up the algorithm. In order to demonstrate the proposed methodology efficiency, it was tested in two systems, the two areas Kundur system and the IEEE 39 bus system. The results are compared against the results of the classic methodology used in operation centers. Through these results it is possible to show the possibility of their use in real time and elucidate the major improvements resulting from the proposed development

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Companhia Estadual de Distribuicao de Energia Eletrica do Rio Grande do Sul (CEEE-D)[TPWRD-00466-2007

Extended Fault-Location Formulation for Power Distribution Systems

In this paper, an extended impedance-based fault-location formulation for generalized distribution systems is presented. The majority of distribution feeders are characterized by having several laterals, nonsymmetrical lines, highly unbalanced operation, and time-varying loads. These characteristics compromise traditional fault-location methods performance. The proposed method uses only local voltages and currents as input data. The current load profile is obtained through these measurements. The formulation considers load variation effects and different fault types. Results are obtained from numerical simulations by using a real distribution system from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), Southern Brazil. Comparative results show the technique robustness with respect to fault type and traditional fault-location problems, such as fault distance, resistance, inception angle, and load variation. The formulation was implemented as embedded software and is currently used at CEEE-D`s distribution operation center.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Companhia Estadual de Distribuicao de Energia Eletrica do Rio Grande do Sul (CEEE-D)[TPWRD-00673-2007

Unbalanced Underground Distribution Systems Fault Detection and Section Estimation

Abstract. This paper presents a novel fault detection and section estimation method for unbalanced underground distribution systems (UDS). The method proposed is based on artificial neural networks (ANNs) and wavelet transforms (WTs). The majority of UDS are characterized by having several single/double phase laterals and non-symmetrical lines. Also, Digital Fourier Transforms (DFT), used in the majority of traditional protection relays, supplies a low level of robustness to the fault diagnosis process due to its inversely proportional time-frequency characteristic. These characteristics compromise the traditional fault diagnosis methods performance. ANNs are capable of learning and generalizing, whereas WTs are robust tools capable of evaluating a signal's frequency range that can characterize the fault phenomenon. This paper describes the proposed diagnosis method and discusses the results obtained from simulated implementation. The obtained results demonstrate the capability and robustness of the technique indicating its potential for on-line applications