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Bad data detection, identification and correction in distribution system state estimation based on PMUs

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Abstract

This paper presents a novel approach for bad data correction in state estimation (SE) for three-phase distribution systems. Based on an optimization model, a SE technique is presented considering branch currents as state variables to be estimated in regular time intervals. In this work, the presence of gross errors is detected by a comparative analysis of the objective function with a threshold value determined by Monte Carlo simulations assuming different load scenarios and Gaussian aleatory errors associated with the measurements gathered from the network. A novel index is proposed for identifying the corrupted measurements based on their corresponding largest residuals. For bad data correction, a new procedure is presented based on statistical analysis of the measurements variation along the time. Computational simulations are carried out using the IEEE 33-bus test system in order to prove the efficiency of the proposed methodology. The main contribution of this paper is the development of a gross error correction technique for SE assuming a limited number of phasor measurement units allocated along the feeders considering all the peculiarities of unbalanced distribution networks. This feature ensures that estimation errors lower than 1% are provided for network operators eliminating the effect of bad data in the SE process.

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Acknowledgements

The authors would like to thank Jose Luiz Rezende Pereira (in memorium) for all his precious contribution to this work.

This project is funded by TBE group companies from the R&D ANEEL project, “PD-02651-0016 / 2018 - Development of a power quality monitoring and a decision taking system for transmission lines”. The authors would like to thank CAPES, CNPq, FAPEMIG and INERGE for supporting this research.

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Authors and Affiliations

  1. Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ), Rio de Janeiro, Brazil

    Bráulio César de Oliveira

  2. Federal University of Juiz de Fora, Juiz de Fora, Brazil

    Igor D. Melo & Matheus A. Souza

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  1. Bráulio César de Oliveira
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  2. Igor D. Melo
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  3. Matheus A. Souza
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Correspondence to Bráulio César de Oliveira.

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The authors would like to thank Jose Luiz Rezende Pereira (in memorium) for all his precious contribution to this work.

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de Oliveira, B.C., Melo, I.D. & Souza, M.A. Bad data detection, identification and correction in distribution system state estimation based on PMUs. Electr Eng 104, 1573–1589 (2022). https://doi.org/10.1007/s00202-021-01406-2

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