In many applications of power quality monitoring, distributed measurement systems are required to provide an evaluation of the harmonic status of the system. Anyway, in distribution systems, only a few network nodes can, with acceptable costs, be equipped with measurement devices. As a consequence, lack of information has to be covered by means of suitable Harmonic State Estimation (HSE) techniques. An optimization algorithm is proposed to deals with the problem of choosing, at the lowest possible cost, the optimal number and position of measurement instruments. Such devices should allow HSE algorithms to provide results having a prefixed level of accuracy. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. Simulation results on a benchmark distribution network show the validity of the proposed approach.

Optimal measurement devices allocation for harmonic state estimation considering parameters uncertainty in distribution networks

MUSCAS, CARLO;PILO, FABRIZIO GIULIO LUCA;PISANO, GIUDITTA;SULIS, SARA
2007-01-01

Abstract

In many applications of power quality monitoring, distributed measurement systems are required to provide an evaluation of the harmonic status of the system. Anyway, in distribution systems, only a few network nodes can, with acceptable costs, be equipped with measurement devices. As a consequence, lack of information has to be covered by means of suitable Harmonic State Estimation (HSE) techniques. An optimization algorithm is proposed to deals with the problem of choosing, at the lowest possible cost, the optimal number and position of measurement instruments. Such devices should allow HSE algorithms to provide results having a prefixed level of accuracy. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. Simulation results on a benchmark distribution network show the validity of the proposed approach.
2007
978-84-690-9441-9
Dynamic programming; Harmonic State Estimation; Monte Carlo methods; Network parameters; Optimal meter placement
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/104065
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