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Bayesian Entropy Methodology: A Novel Approach to Setting Anti-Islanding Protections with Enhanced Stability and Sensibility

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  • Eduardo Marcelo Seguin Batadi

    (Instituto de Energía Eléctrica (IEE), Universidad Nacional de San Juan (UNSJ) and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Juan J5400, Argentina)

  • Maximiliano Martínez

    (Instituto de Energía Eléctrica (IEE), Universidad Nacional de San Juan (UNSJ) and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Juan J5400, Argentina)

  • Marcelo Gustavo Molina

    (Instituto de Energía Eléctrica (IEE), Universidad Nacional de San Juan (UNSJ) and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Juan J5400, Argentina)

Abstract

The risk of unintentional islanding creation in distributed energy systems poses a significant security concern since unintentional islanding formation could lead to a supply of energy outside of the optimal quality limits. This constitutes a risk for users, maintenance personnel, infrastructure, and devices. To mitigate this problem, anti-islanding protections are widely used to prevent the distributed generator from feeding a portion of the radial distribution grid when a protection device trips upstream. However, the effectiveness of these protections heavily relies on properly tuning protection setting thresholds (such as time delay and pickup). This work proposes a novel approach that utilizes entropy as a model and metric of the uncertainty associated with a particular protection setting. By minimizing entropy, the proposed method aims to improve stability and sensitivity, consequently improving the overall performance of anti-islanding protection. Simulation results demonstrate that the Bayesian entropy methodology (BEM) approach achieves enhanced stability in various scenarios, including frequency transients, and demonstrates a notable reduction in the size of the dataset and computational burden, ranging between 91% and 98%, when compared to related works, with an improvement of the uncertainty achieved. The findings of this study contribute to the development of more robust and reliable anti-islanding protections.

Suggested Citation

  • Eduardo Marcelo Seguin Batadi & Maximiliano Martínez & Marcelo Gustavo Molina, 2024. "Bayesian Entropy Methodology: A Novel Approach to Setting Anti-Islanding Protections with Enhanced Stability and Sensibility," Energies, MDPI, vol. 17(3), pages 1-26, January.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:3:p:693-:d:1330722
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    References listed on IDEAS

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