Automata-based reasoning for the diagnosis of short circuits in power transmission networks

P.Baroni, G. Lamperti, P. Pogliano, G. Tornielli, M. Zanella

Proc. AIENG 1997, 12th International Conference on the Applications of Artificial Intelligence in Engineering, Capri, I, Luglio 1997, 415-440

 

Abstract

This document introduces an original technique for short circuit diagnosis in power transmission networks. The basic idea is that the diagnostic task cna be conveniently viewed as a multi-layer interpretation process of available observations, at the end of which, as a sort of harvest, relevant diagnostic information can be gathered to generate the required diagnosis. Three different interpretation layers are considered: local interpretation, global interpretation, and heuristic interpretation. This paper presents the first (application independent) two layers. The local interpretation focuses on the behaviour of single protection components that are distributed in the power network and operate when a short circuit occur. The global interpretation provides a global behavior of the protection apparatus by combining consistent local behaviours so that given interface constraints are met. Finally, the heuristic interpretation is meant both to shrink the cardinality of the global interpretation, by eliminating a number of spurious global behaviors on the basis of application-dependent heuristic constraints, and to eventually localize the short circuit and possibly faulty protection components within the transmission network. The implementation of the proposed technique is under way. The resulting system is going to be tested by ENEL, the Italian electricity board, using the transmission network of part of northern Italy.

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