Techniques able to assess distribution networks reliability have to be adapted to the Smart Grid paradigm that is going to be implemented in real scenarios in the next future. In this perspective, an algorithm for distribution systems reliability assessment in the presence of distributed generators, accounting for islanding operation too, is presented in this paper. The procedures of the algorithm are the core of an analytical method and random/sequential Monte Carlo simulation methods developed by the authors in previous works. These methods are based on two elements: the first one is a generalized systematic approach able to identify the fault effect on a network’s node thanks to some topological rules (called "cases") applicable to any radial network; the second one is a technique to faster compute reliability indices by aggregating faulted branches (called "set of branches") and nodes (called "set of nodes"). The paper proposes two automatic and general procedures to identify the cases and the sets, which are useful for implementation of both analytical and Monte Carlo simulation methods. © 2015 School of Electrical Engineering and Informatics. All rights reserved.

An algorithm for reliability assessment of distribution systems in presence of distributed generators.

CONTI, Stefania;Rizzo S. A.
2015

Abstract

Techniques able to assess distribution networks reliability have to be adapted to the Smart Grid paradigm that is going to be implemented in real scenarios in the next future. In this perspective, an algorithm for distribution systems reliability assessment in the presence of distributed generators, accounting for islanding operation too, is presented in this paper. The procedures of the algorithm are the core of an analytical method and random/sequential Monte Carlo simulation methods developed by the authors in previous works. These methods are based on two elements: the first one is a generalized systematic approach able to identify the fault effect on a network’s node thanks to some topological rules (called "cases") applicable to any radial network; the second one is a technique to faster compute reliability indices by aggregating faulted branches (called "set of branches") and nodes (called "set of nodes"). The paper proposes two automatic and general procedures to identify the cases and the sets, which are useful for implementation of both analytical and Monte Carlo simulation methods. © 2015 School of Electrical Engineering and Informatics. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/17680
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