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2019
Journal Article
Title
Robustness conditions of LPV fault estimation systems for renewable microgrids
Abstract
As displayed in recent literature, Fault Estimation schemes can be designed for renewable microgrids considering the use of multiple Linear Parameter Varying (LPV) observers, derived from Linear Matrix Inequalities for the mixed H^2/H^∞
norm minimization. In this work, the study of such observers is extended: now, such method is discussed in terms of Robustness, using the Small Gain Theorem and -analysis. The possibility of uncertainties that may arise on Energy Hub models is discussed, in terms of unrealistic assumptions in the modelling/identification phase. Via frequencial analysis, this study also investigates the effect of noise and load disturbances upon fault estimation in the uncertain (model/plant-mismatch) situations. High-fidelity simulations are also presented to assess the robustness qualities of such LPV observer method, whilst the noticeable performance deterioration is quantified.
norm minimization. In this work, the study of such observers is extended: now, such method is discussed in terms of Robustness, using the Small Gain Theorem and -analysis. The possibility of uncertainties that may arise on Energy Hub models is discussed, in terms of unrealistic assumptions in the modelling/identification phase. Via frequencial analysis, this study also investigates the effect of noise and load disturbances upon fault estimation in the uncertain (model/plant-mismatch) situations. High-fidelity simulations are also presented to assess the robustness qualities of such LPV observer method, whilst the noticeable performance deterioration is quantified.
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