Abstract
We introduce a new perspective to improve the reliability of a network, which aims at finding cost-effective portfolios of Prognostics and Health Management (PHM) systems to be installed throughout the network. To do this, we estimate the reliability of the single network element equipped with a PHM system, whose prognostic performance is measured in terms of the α−λ performance, false positive and false negative metrics. Then, we apply genetic algorithms for finding the portfolios of PHM systems to be installed on the network elements, which are optimal with respect to cost and a global reliability efficiency index of the network. The workbench case study of the IEEE 14 bus network is considered as application.
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