The growing demand for improved quality of service increases the importance of network automation. These allow improving the fault isolation and reconfiguration time and therefore increasing the system quality of service. Since the investment in remote-controlled switch (RCS) devices comes at a cost, this paper proposes a heuristic approach to solve the problem of optimal siting RCS devices in distribution systems. For doing that, RCS devices are located to improve the reliability of the system based on the optimal open ties deriving from the Distribution Network (DN) reconfiguration problem. A Genetic Algorithm (GA) has been developed to optimize the radial layout of the DN taking into account the reliability of the system. As a measure of the system reliability, we use a risk index which is expected to well estimate, based on the statistical data available, the System Average Interruption Frequency Index (SAIFI). The risk index is based on two parameters: the length of the feeders, which measures the failure probability, and the number of customers, which measures the failure impact. The solution approach has been tested on a real distribution subsystem of Milano.

Optimal procedure for remote-controlled switch devices siting in distribution systems using heuristic algorithms

Alessandro Bosisio;
2020-01-01

Abstract

The growing demand for improved quality of service increases the importance of network automation. These allow improving the fault isolation and reconfiguration time and therefore increasing the system quality of service. Since the investment in remote-controlled switch (RCS) devices comes at a cost, this paper proposes a heuristic approach to solve the problem of optimal siting RCS devices in distribution systems. For doing that, RCS devices are located to improve the reliability of the system based on the optimal open ties deriving from the Distribution Network (DN) reconfiguration problem. A Genetic Algorithm (GA) has been developed to optimize the radial layout of the DN taking into account the reliability of the system. As a measure of the system reliability, we use a risk index which is expected to well estimate, based on the statistical data available, the System Average Interruption Frequency Index (SAIFI). The risk index is based on two parameters: the length of the feeders, which measures the failure probability, and the number of customers, which measures the failure impact. The solution approach has been tested on a real distribution subsystem of Milano.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1464769
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