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The integration of an ever-growing proportion of large-scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With reduced inertia due to nonsynchronous penetration in a power grid, system-wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide-area phase-angle measurements. This is challenging since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis, is proposed to model the time-varying and nonlinear trends in the voltage-phase angle data. The effectiveness of the technique is exemplified using DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.
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Liu et al. (2016) studied this question.
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