A Probabilistic Assessment Method for Voltage Stability Considering Large Scale Correlated Stochastic Variables

Autor: Jing Zhang, Luqin Fan, Ying Zhang, Gang Yao, Peijia Yu, Guojiang Xiong, Ke Meng, Xiangping Chen, Zhaoyang Dong
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: IEEE Access, Vol 8, Pp 5407-5415 (2020)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2963280
Popis: Voltage stability has always been one of the most important concerns. As the increasing integration of large-scale renewable energy sources in power systems, the correlation between load demands and renewable energy systems becomes more and more complex and important for probabilistic voltage stability. There are two significant issues for probabilistic voltage stability assessment: (i) how to choose the reasonable power increment direction which determines the reliability of voltage stability assessment when considering the actual operating characteristics of the power system; and (ii) how to obtain the samples characterized with the specified distribution and the desired correlation. We propose methodologies to define the reasonable power increment direction with theoretical proof. Moreover, power method transformation combined with Latin hypercube sampling and twice-permutation technique is proposed for probabilistic voltage stability assessment. Case studies with two modified IEEE test systems show that the proposed method is accurate and efficient.
Databáze: Directory of Open Access Journals