Embedded Application for Power Flow Variability Assessment

The evaluation of low voltage (LV) distribution power grids needs precise power profiles not only for installed power generation, including renewable sources but also for individual and combined loads. Traditional power system analysis methods generally operate under the assumption of a steady-state condition between consecutive measurements. To verify the assumption that the system conforms to this predefined model, statistical metrics can be used. In this paper, some of these metrics (CV(RMSD) and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R^{2}$</tex>) are integrated as part of an application that can be embedded in state-of-the-art smart meters.

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Published
2024-10-24
DOI
https://doi.org/10.1109/icate62934.2024.10749285
Primary Topic
Real-time simulation and control systems
Type
article
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article

Embedded Application for Power Flow Variability Assessment

Ana-Maria Dumitrescu, Anca Petruța Brîncoveanu
Real-time simulation and control systems
article

Embedded Application for Power Flow Variability Assessment

Ana-Maria Dumitrescu, Anca Petruța Brîncoveanu
article en

Abstract

The evaluation of low voltage (LV) distribution power grids needs precise power profiles not only for installed power generation, including renewable sources but also for individual and combined loads. Traditional power system analysis methods generally operate under the assumption of a steady-state condition between consecutive measurements. To verify the assumption that the system conforms to this predefined model, statistical metrics can be used. In this paper, some of these metrics (CV(RMSD) and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R^{2}$</tex>) are integrated as part of an application that can be embedded in state-of-the-art smart meters.

Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Affordable and clean energy
Openalex Percentile: Top 76%
Real-time simulation and control systems
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