2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502)
DOI: 10.1109/ptc.2001.964909
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Exploring fuzzy relations for alarm processing and fault location in electrical power systems

Abstract: This work investigates the construction of fuzzy relations for alarm processing and fault location in electrical power systems. Several data aggregation classes are tested and compared. Fuzzy relations are established with the aid of the knowledge on protection devices operation for faults involving different system components. Tests are performed with a 7-bus test system and with part of a real brazilian system.

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Cited by 12 publications
(9 citation statements)
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“…However, those methods are not capable of performing well in the presence of corrupted/lost data. This work extends the ideas presented in [10] and [17] and proposes a new methodology based on ANN and fuzzy logic for alarm processing and identification of faulted components in power systems. Fuzzy logic allows one to take into account qualitative information provided by human experts, such as experienced operators.…”
Section: Introductionmentioning
confidence: 77%
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“…However, those methods are not capable of performing well in the presence of corrupted/lost data. This work extends the ideas presented in [10] and [17] and proposes a new methodology based on ANN and fuzzy logic for alarm processing and identification of faulted components in power systems. Fuzzy logic allows one to take into account qualitative information provided by human experts, such as experienced operators.…”
Section: Introductionmentioning
confidence: 77%
“…Adaptability may be achieved through the use of parameterized families of operators, which may be very useful for obtaining membership functions in a variety of problems. In [17], a simulation study has been carried out to compare four families of operators with respect to their capability of obtaining fuzzy relations among alarm patterns and possibly faulted system components. Among the tested families, the Hamacher's model [20], with parameter , was found to be the most adequate.…”
Section: A Construction Of the Fuzzy-based Training Setmentioning
confidence: 99%
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“…The applications of artificial intelligent for fault location have been proposed. The application of fuzzy relations for fault [2,5]. They investigated the construction of fuzzy relations for alarm processing and fault location in electrical power systems.…”
Section: Introductionmentioning
confidence: 99%
“…In the case of disturbances, faulted components must be isolated very quickly in order to reduce the risk of damage in system electrical devices. Besides that, the interruption of energy supply must be minimize or avoided [2]. The protection devices should operate in a coordinated scheme, to guarantee that only the faulted components are disconnected.…”
Section: Introductionmentioning
confidence: 99%