Ghendy Cardoso

Application of neural-network modules to electric power system fault section estimation

This paper presents a neural system intended to aid the control center operator in the task of fault section estimation. Its analysis is based on information about the operation of protection devices and circuit breakers. In order to allow the diagnosis task, the protection system philosophy of busbars, transmission lines, and transformers are modeled with the use of two types of neural networks: the general regression neural network and the multilayer perceptron neural network. The tool described in this paper can be applied to real bulk power systems and is able to deal with topological changes without having to retrain the neural networks.

An Innovative Loss-of-Excitation Protection Based on the Fuzzy Inference Mechanism

A new loss-of-excitation protection based on fuzzy set theory has been presented. It makes use of conventional concepts of loss-of-excitation protection in synchronous generators (i.e., the behavior of internal voltage and apparent impedance trajectory). Instead of crisp values, a fuzzy inference mechanism is applied. To show the effectiveness of the proposed technique, comparisons are made with traditional protection methods by considering different generators sizes. The protection scheme proposed displays a secure and effective high-speed loss-of-excitation detection during power swings. Furthermore, the performance of the proposed method was not affected by generator parameters.

Identifying the Primary Fault Section After Contingencies in Bulk Power Systems

This paper deals with the problem of fault section estimation in electric power systems, undertaken at a control center level and using information about the operation of protection relays and circuit breakers. The developed methodology should be used after the occurrence of contingencies with definitive disconnections, and before beginning the process of network restoration. Due to the absence of an analytic formulation, the problem calls for the use of artificial-intelligence techniques, such as neural networks and expert systems. Neural networks are employed to model the protection systems, dealing with the uncertainties involved with relay and circuit-breaker operation messages. An expert system is used to complement the results provided by the neural networks, considering the network topology. The results show that the developed methodology is applicable to real large-scale power systems. In addition, it is capable of noise suppression in relay and circuit-breaker trip messages, treats multiple faults naturally, and infers a solution even in cases when remote backup protection action occurs.

CT Saturation Detection Based on the Distance Between Consecutive Points in the Plans Formed by the Secondary Current Samples and Their Difference-Functions

This paper proposes a novel method to detect the saturation intervals where the secondary current of current transformers for protection purposes becomes distorted. The method is based on the analysis of plans formed by the secondary current samples (i2) and their difference-functions (del[n]). The distance between consecutive points in these plans has a significant increase when saturation occurs, bucking the trend of the intervals without saturation. Two plans are considered: del[2] versus del[1] and del[3] versus del[2]. Besides the ease of implementation, the results indicate the effectiveness of the method to detect saturation intervals.

Passive Method for Distributed-Generation Island Detection Based on Oscillation Frequency

This paper aims to present a passive island detection technique for synchronous distributed generation (DG). The technique is based on frequency oscillation estimation in order to distinguish the islanding from other events that may occur in distribution systems. The island detection uses a small window to estimate the oscillation frequency, obtaining faster responses than the existing methods which use larger windows to estimate the damping and frequency of oscillation. The algorithm performance has been tested considering different generation and load scenarios, including short circuits, load, and capacitor switching, DG outage, and islanding. The technique is reliable since it does not trip for a nonislanding event; the island detection time is less than 40 ms and its nondetection zone is less than 1.6% of the DG nominal power. The proposed method has been compared with one of the most common algorithms used in practice-the rate of change of frequency. The results show that the algorithm based on frequency oscillation detection performs better than the ROCOF, and its mathematical simplicity is adequate for practical relay implementation.

Alarm processing and fault diagnosis in power systems using Artificial Neural Networks and Genetic Algorithms

This work approaches relative aspects to the alarm processing problem and fault diagnosis in system level, having as purpose filter the alarms generated during a outage and identify the equipment under fault. A methodology was developed using Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in order to resolve the problem. This procedure had as initiative explore the GA capacity to deal with combinatory problems, as well as the ANN processing speed and generalization capacity. Such strategy favors a fast and robust solution.

New setting of loss of excitation protection in P-Q plan in order to maximize the operation area of the capacity curve of the synchronous machine

This paper presents a method for maximizing the operation area of the capacity curve of a synchronous machine. The technique is set in P-Q plan in order to adjust more features of minimum excitation and practical stability limits of the capacity curve. Thus, the voltage limiter can be intended to the left of the capacity curve and so the machine may have an operating gain in this region. The new setting is done primarily on the generator capacity curve, plan P-Q, and subsequently analyzed in the R-X plan.

RESSECÇÃO PULMONAR EM CÃES: ESTUDO EXPERIMENTAL

The prupose of this study was to investigate physiological changes post-pulmonary ressections, measured toward, current volume, mean arterial pressure, central venous pressure, radiology, blood gases. In this study, three series of clinical healthy mongrel dog (three male and tive female) were submitted to lobectomy, bilobectomy and pneumonectomy, each animal serving as it own control. An increase of the current volume in all dogs operated. Was detected pulmonary edema associated with respiratory acidosis and hipoxic were observed in bilobectomy and pneumonectomy resulted of lung ressections and changes perfusions.

Transients detection and classification in distribution networks for high impedance faults identification

Protection systems used in distribution networks are not able to detect short circuits with high contact resistance due to reduced currents generated, endangering the population and degrading the quality of the energy supplied. In this sense, this paper presents a new technique for detecting high impedance faults (HIF). The major advantage of this method is the not needing of additionally equipment installation in the distribution network, which reduces the cost of its implementation. Moreover, the proposed methodology is immune to any electrical transients generated in the system, such as capacitor bank switching, power transformers and inputs and output loads.

Binary integer programming applied to fault section estimation in power systems

This paper proposes a novel methodology for fault section estimation in electrical power systems based on binary integer programming (BIP). The operators of control centers are sometimes overloaded by the number of alarm messages produced when protection operate to clear faults. The main motivation for this work is the development of an alarm processing tool to support the operator decisions after disturbances in order to enhance the service reliability and reduce the power restoration time. The BIP model classifies SCADA alarms to estimate the faulted section and also to identify the malfunctioned protective devices. Possible fault scenarios were considered in part of a real Brazilian power system to validate the methodology. The results show that the proposed approach can find the optimal solution even in case of multiple faults or in case of protection devices failures.