Impact of Cascade Disconnection of Distributed Energy Resources on Bulk Power System Stability: Modeling and Mitigation Requirements

Mourinho, Fabricio Andrade; Assis, Tatiana M. L.

doi:10.35833/mpce.2022.000365

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…In [51], a methodology based on dynamic security regions is presented to identify the minimum requirements for RoCoF-based (ANSI 81R) anti-islanding protections for DERs that ensure the safe operation of the Brazilian Interconnected Power System. While this methodology successfully identified minimal safety conditions for setting the lowest RoCoF thresholds, it did not provide an analysis of the performance of these settings in terms of sensitivity across various islanding scenarios, relegating the contribution of this work solely to the analysis of security in the EPS.…”

Section: Literature Review Of Islanding Detection Methodsmentioning

confidence: 99%

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

Seguin Batadi,

Martínez,

Molina

2024

Energies

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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.

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Section: Literature Review Of Islanding Detection Methodsmentioning

confidence: 99%