Generated power-based composite security index for evaluation of cascading outages

Ibrahim, Hamed A.; Hemade, Bassam A.; Talaat, H.

doi:10.1109/mepcon.2017.8301263

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…However, it found suffering terribly from the masking effect problem [29,30], which makes performance index results questionable. In contrast, robust indices have been presented in [51,52]. Compared with the performance index in [3], the performance of the composite insecurity index (CISI) in [51,52] was found superb and comprehensive.…”

Section: Composite Insecurity Indexmentioning

confidence: 98%

“…In contrast, robust indices have been presented in [51,52]. Compared with the performance index in [3], the performance of the composite insecurity index (CISI) in [51,52] was found superb and comprehensive. CISI defined in terms of the thermal limit of transmission lines, voltage profile at each bus, active and reactive power of the generation unit.…”

Section: Composite Insecurity Indexmentioning

confidence: 98%

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Conceptual Analysis of Different Clustering Techniques for Static Security Investigation

Hemade¹,

Ibrahim²,

Talaat³

2019

IJISA

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Power system contingency studies play a pivotal role in maintaining the security and integrity of modern power system operation. However, the number of possible contingencies is enormous and mostly vague. Therefore, in this paper, two well-known clustering techniques namely K-Means (KM) and Fuzzy C-Means (FCM) are used for contingency screening and ranking. The performance of both algorithms is comparatively investigated using IEEE 118-bus test system. Considering various loading conditions and multiple outages, the IEEE 118-bus contingencies have been generated using fast-decoupled power flow (FDPF). Silhouette analysis and fuzzy partition coefficient techniques have been profitably exploited to offer an insight view of the number of centroids. Moreover, the principal component analysis (PCA) has been used to extract the dominant features and ensure the consistency of passed data with artificial intelligence algorithms' requirements. Although analysis of comparison results showed excellent compatibility between the two clustering algorithms, the FCM model was found more suitable for power system static security investigation.

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Section: Composite Insecurity Indexmentioning

confidence: 98%

Section: Composite Insecurity Indexmentioning

confidence: 98%

Conceptual Analysis of Different Clustering Techniques for Static Security Investigation

Hemade¹,

Ibrahim²,

Talaat³

2019

IJISA

Self Cite

View full text Add to dashboard Cite

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Hierarchical Clustering-Based Framework for Interconnected Power System Contingency Analysis

et al. 2022

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This paper investigates a conceptual, theoretical framework for power system contingency analysis based on agglomerative hierarchical clustering. The security and integrity of modern power system networks have received considerable critical attention, and contingency analysis plays a vital role in assessing the adverse effects of losing a single element or more on the integrity of the power system network. However, the number of possible scenarios that should be investigated would be enormous, even for a small network. On the other hand, artificial intelligence (AI) techniques are well known for their remarkable ability to deal with massive data. Rapid developments in AI have led to a renewed interest in its applications in many power system studies over the last decades. Hence, this paper addresses the application of the hierarchical clustering algorithm supported by principal component analysis (PCA) for power system contingency screening and ranking. The study investigates the hierarchy clustering under different clustering numbers and similarity measures. The performance of the developed framework has been evaluated using the IEEE 24-bus test system. The simulation results show the effectiveness of the proposed framework for contingency analysis.

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Generated power-based composite security index for evaluation of cascading outages

Cited by 2 publications

References 21 publications

Conceptual Analysis of Different Clustering Techniques for Static Security Investigation

Conceptual Analysis of Different Clustering Techniques for Static Security Investigation

Hierarchical Clustering-Based Framework for Interconnected Power System Contingency Analysis

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