The islanded micro‐grid large signal stability analysis based on neuro‐fuzzy model

Abstract

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.

Large-Signal Stable Nonlinear Control of DC/DC Power Converter With Online Estimation of Uncertainties

“…Indeed, the large-signal stability proof implies the smallsignal stability, but the other way around is not sure [37], [38]. Since a large-signal stable system is naturally small-signal stable, the method proposed in this paper can indeed solve the small-signal stability issue, so no small-signal stability analysis is required.…”