arXiv Open Access 2025

Efficient Probabilistic Assessment of Power System Resilience Using the Polynomial Chaos Expansion Method with Enhanced Stability

Aidan Gerkis Xiaozhe Wang
Lihat Sumber

Abstrak

Increasing frequency and intensity of extreme weather events motivates the assessment of power system resilience. The random nature of power system failures during these events mandates probabilistic resilience assessment, but state-of-the-art methods are computationally inefficient. In this paper, an enhanced PCE method to quantify power system resilience based on the extended AC Cascading Failure Model (AC-CFM) model is proposed. To address repeatability issues arising from PCE computation with different sample sets, we propose a novel experiment design method. Numerical studies on the IEEE 39-bus system illustrate the improved repeatability and convergence of the method. The enhanced PCE method is then used to efficiently assess the system's resilience and propose adaptation measures.

Topik & Kata Kunci

Penulis (2)

A

Aidan Gerkis

X

Xiaozhe Wang

Format Sitasi

Gerkis, A., Wang, X. (2025). Efficient Probabilistic Assessment of Power System Resilience Using the Polynomial Chaos Expansion Method with Enhanced Stability. https://arxiv.org/abs/2501.09857

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
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Open Access ✓