Open AccessThe islanded micro‐grid large signal stability analysis based on neuro‐fuzzy model
Author(s) -
Ahmadi Hadi,
Kazemi Ahad
Publication year - 2020
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12449
Subject(s) - control theory (sociology) , grid , fuzzy logic , computer science , stability (learning theory) , artificial neural network , identification (biology) , signal (programming language) , electric power system , lyapunov function , mathematical optimization , power (physics) , mathematics , nonlinear system , artificial intelligence , machine learning , geometry , programming language , botany , control (management) , physics , quantum mechanics , biology
Summary 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.