Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Y. Guo, K. Li, D. M. Laverty, Y. Xue

Research output: Contribution to journalArticle

50 Citations (Scopus)
697 Downloads (Pure)

Abstract

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.
Original languageEnglish
Pages (from-to)2544 - 2552
JournalIeee Transactions On Power Delivery
Volume30
Issue number6
Early online date20 May 2015
DOIs
Publication statusPublished - Dec 2015

Bibliographical note

Distribution generation and significant penetration of renewable energies have imposed significant challenges to the operation and control of traditional power systems. Unintentional islanding of distributed generators may pose significant safety and system operation issues. This paper proposes a Recursive principal component analysis scheme for reliable islanding detection, verified by detecting abnormal transients occurring in the UK utility network using data recorded by the Open-PMUs (phasor measurement units) developed at Queen’s University Belfast, as a joint effort from both UK and China team, under the auspice of the EPSRC-NSFC jointly funded large scale project on electric vehicles and smart grid (EP/L001063/1).

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