Uncertain Impedances Propagation in Power Flow by Polynomial Chaos Expansion

Distribution networks are integrating a growing number of flexible consumers and distributed generation, opening the possibility for their management. However, instrumentation is very scarce in distribution areas. As lines have a very long service life, their impedances cannot be assumed to be perfectly known. This study therefore proposes to introduce into the power flow equations a source of uncertainty arising from the impedances values. This stochastic power flow is solved using Polynomial Chaos Expansion. The accuracy of this method is confirmed on a case study, along with its numerical efficiency. It is also revealed to be capable of adapting to very high impedance variances, as well as to asymmetric distributions with discontinuities.

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Published
2025-06-29
DOI
https://doi.org/10.1109/powertech59965.2025.11180448
Primary Topic
Smart Grid and Power Systems
Type
article
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article

Uncertain Impedances Propagation in Power Flow by Polynomial Chaos Expansion

Roman Le Goff Latimier, T. Brembilla
Smart Grid and Power Systems
article

Uncertain Impedances Propagation in Power Flow by Polynomial Chaos Expansion

Roman Le Goff Latimier, T. Brembilla
article en

Abstract

Distribution networks are integrating a growing number of flexible consumers and distributed generation, opening the possibility for their management. However, instrumentation is very scarce in distribution areas. As lines have a very long service life, their impedances cannot be assumed to be perfectly known. This study therefore proposes to introduce into the power flow equations a source of uncertainty arising from the impedances values. This stochastic power flow is solved using Polynomial Chaos Expansion. The accuracy of this method is confirmed on a case study, along with its numerical efficiency. It is also revealed to be capable of adapting to very high impedance variances, as well as to asymmetric distributions with discontinuities.

Centre National de la Recherche Scientifique (FR), Institut d'Électronique et des Technologies du numéRique (FR), Université de Rennes (FR)
Openalex Percentile: Top 72%
Smart Grid and Power Systems
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