A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids

Ali, Mazhar; Dimitrovski, Aleksandar; Qu, Zhihua; Sun, Wei

doi:10.1109/pesgm52003.2023.10253169

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A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids

Ali, Mazhar·Dimitrovski, Aleksandar·Qu, Zhihua·Sun, Wei

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Abstract

Active distribution grids are gaining traction to meet the growing environmental, socio-economic, and sustainability targets. Various advanced smart grid technologies facilitate the integration of Distributed Energy Resources (DERs) by supporting the bi-directional power flow. The limited observability of distribution grids, primarily related to their location at the very edge of power system infrastructure, brings challenges to optimal grid management. Moreover, only a limited number of measurements at regular intervals are usually available. This paper presents a novel inference framework, referred to as “Voltage Inference”, to overcome the observability issues. The proposed framework employs a prediction step based on the Multivariate Taylor series approximation, followed by a corrector step that minimizes the estimation error to infer the otherwise unknown voltages from the available measurements. Furthermore, numerical results on the IEEE 13-bus test feeder validate the accuracy and computational performance of the proposed framework.

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Ali, Mazhar, Dimitrovski, Aleksandar, Qu, Zhihua, Sun, Wei. 2023-07-16. A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids. https://doi.org/10.1109/pesgm52003.2023.10253169

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