Abstract
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 non-synchronous 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 both DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.
| Original language | English |
|---|---|
| Pages (from-to) | 1901-1911 |
| Number of pages | 11 |
| Journal | Ieee Transactions On Power Delivery |
| Volume | 31 |
| Issue number | 4 |
| Early online date | 14 Jan 2016 |
| DOIs | |
| Publication status | Published - Aug 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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Dive into the research topics of 'Wide-Area Phase-Angle Measurements for Islanding Detection—An Adaptive Nonlinear Approach'. Together they form a unique fingerprint.Profiles
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Xueqin Amy Liu
- School of Electronics, Electrical Engineering and Computer Science - Senior Lecturer
- Energy Power and Intelligent Control
Person: Academic
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