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The islanded micro‐grid large signal stability analysis based on neuro‐fuzzy model
International Transactions on Electrical Energy Systems ( IF 2.3 ) Pub Date : 2020-05-01 , DOI: 10.1002/2050-7038.12449
Hadi Ahmadi 1 , Ahad Kazemi 1
Affiliation  

The study and identification of stability condition in an islanded micro‐grid are critical due to the lack of generation resources and load changes. On the other hand, the output power of the renewable units and the load level in a micro‐grid are uncertain and the system does not have a dominant operating point. Therefore, small signal analysis methods results have small validity range and cannot be generalized to the whole system. Therefore, a Lyapunov function (LF) based large signal stability method is proposed in this article to address the problem of small signal methods. Also, a Neuro‐Fuzzy system is proposed to consider uncertainties and network modeling. In this study, the Takagi‐Sugeno (T‐S) fuzzy system is used. Artificial neural network is also applied to provide an optimal tool for identifying system uncertainties, while T‐S rules are used to provide a framework of previous knowledge of the system. The main purpose is to propose an identification and modeling process to study the stability condition and boundaries in an islanded micro‐grid. After the uncertain system is modeled, the system LF is calculated using Linear Matrix Inequality and the system domain of attraction is determined.

中文翻译:

基于神经模糊模型的孤岛微电网大信号稳定性分析

由于缺乏发电资源和负荷变化,在孤岛微电网中研究和确定稳定状态至关重要。另一方面,可再生单元的输出功率和微电网中的负载水平不确定,并且系统没有主要的工作点。因此,小信号分析方法的结果有效范围小,不能推广到整个系统。因此,本文提出了一种基于李雅普诺夫函数(LF)的大信号稳定方法,以解决小信号方法的问题。此外,提出了一种神经模糊系统来考虑不确定性和网络建模。在本研究中,使用了Takagi-Sugeno(TS)模糊系统。人工神经网络也可用于提供一种识别系统不确定性的最佳工具,T‐S规则用于提供系统的先前知识框架。主要目的是提出一种识别和建模过程,以研究孤岛微电网中的稳定性条件和边界。对不确定系统建模后,使用线性矩阵不等式计算系统LF并确定系统的吸引域。
更新日期:2020-05-01
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