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arXiv · 2308.09521

Data-driven Topology and Parameter Identification in Distribution Systems with limited Measurements

Steven de Jongh·Felicitas Mueller·Fabian Osterberg·Claudio A. Cañizares·Thomas Leibfried·Kankar Bhattacharya
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Abstract

This manuscript presents novel techniques for identifying the switch states, phase identification, and estimation of equipment parameters in multi-phase low voltage electrical grids, which is a major challenge in long-standing German low voltage grids that lack observability and are heavily impacted by modelling errors. The proposed methods are tailored for systems with a limited number of spatially distributed measuring devices, which measure voltage magnitudes at specific nodes and some line current magnitudes. The overall approach employs a problem decomposition strategy to divide the problem into smaller subproblems, which are addressed independently. The techniques for identifying switch states and system phases are based on heuristics and a binary optimization problem using correlation analysis of the measured time series. The estimation of equipment parameters is achieved through a data-driven regression approach and by an optimization problem, and the identification of cable types is solved using a Mixed-Integer Quadratic Programming solver. To validate the presented methods, a realistic grid is used and the presented techniques are evaluated for their resilience to data quality and time resolution, discussing the limitations of the proposed methods.

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Steven de Jongh, Felicitas Mueller, Fabian Osterberg, Claudio A. Cañizares, Thomas Leibfried, Kankar Bhattacharya. 2023-08-18. Data-driven Topology and Parameter Identification in Distribution Systems with limited Measurements. https://arxiv.org/abs/2308.09521

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