Intelligent system for fault diagnosis on low voltage distribution networks

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Intelligent system for fault diagnosis on low voltage distribution networks

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The task of fault diagnosis on the distribution networks operating at 11 kV and lower voltages is very different from the higher voltage levels because very little telemetered data is available and knowledge of a fault occurrence often depends on customers complaining of loss of supply. Unfortunately, the connectivity of customers to the network is not normally available on geographic information systems (GIS), so connectivity is indirectly established through post codes. A novel kind of object oriented blackboard architecture using deep and shallow knowledge has been developed. The notion of object-oriented active databases has also been introduced. The intelligent system developed can assist the control engineer in diagnosing the fault quickly to ameliorate the immediate effects of the fault. The special feature of this research is that the developed architecture is suitable for any fault diagnosis situation where information of the system is incomplete and is accrued over a period of time. Partial solutions are obtained as the first piece of information is received and these partial solutions are improved as further information is received.

Inspec keywords: object-oriented databases; distribution networks; blackboard architecture; fault diagnosis

Other keywords: intelligent system; low voltage distribution networks; deep knowledge; shallow knowledge; fault diagnosis; object-oriented active databases; object oriented blackboard architecture

Subjects: Object-oriented databases; Distribution networks; Knowledge engineering techniques; Power engineering computing

References

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      • Montakhab, M.R.: `Fault diagnosis in low voltage electricity distribution networks usingartificial intelligence', 1994, PhD, Queen Mary and Westfield College, Department of Electronic Engineering, London.
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