A hybrid intelligent system for fault detection in power systems

Mori, H.; Aoyama, H.; Yamanaka, Tateo; Urano, Shoichi

doi:10.1109/ijcnn.2002.1007472

Cited by 7 publications

(1 citation statement)

References 9 publications

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“…Over the past decade considerable advances have been made in the area of fault detection and isolation [1,2] particularly in the areas of aerospace, nuclear reactors, and process control systems. However, a literature survey reveals that the application of analytical model-based fault detection techniques to power systems is presently at its infancy, although a few applications of neural networks to fault detection in power systems have been reported [3,4]. The fact that conventional dynamic models of power systems as reported in the literature [5,6] are not directly amenable to existing fault detection techniques may be the main reason behind the lack of any major contributions in this area.…”

Section: Introductionmentioning

confidence: 99%

Observer-based fault detection and identification scheme for power systems

Aldeen

Crusca

2006

IEE Proc., Gener. Transm. Distrib.

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A scheme suitable for the detection and identification of faults in power systems is presented. Two notable contributions are made: a remodelling of faulty components of power systems that is applicable to both normal and faulty conditions, and a fault detection scheme for power systems. The faults are modelled as unknown inputs, decoupled from the state and output measurements through coordinate transformations, and then estimated through the use of observer theory. The proposed scheme is applied to a power system consisting of a synchronous generator, an exciter, a turbine and speed-governing system, and a network of lines and loads. The case where faults occur on the transmission network is considered. It is shown that the proposed fault detection procedure allows for the real-time identification of the occurrence of the faults and determines their exact locations. Results of detailed simulation studies involving disturbances and faults occurring in linear and nonlinear models of the power system are presented.

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