Anti-islanding protection is becoming increasingly important due to the rapid installation of distributed generation from renewable resources like wind, tidal and wave, solar PV, bio-fuels, as well as from other resources like diesel. Unintentional islanding presents a potential risk for damaging utility plants and equipment connected from the demand side, as well as to public and personnel in utility plants. This paper investigates automatic islanding detection. This is achieved by deploying a statistical process control approach for fault detection with the real-time data acquired through a wide area measurement system, which is based on Phasor Measurement Unit (PMU) technology. In particular, the principal component analysis (PCA) is used to project the data into principal component subspace and residual space, and two statistics are used to detect the occurrence of fault. Then a fault reconstruction method is used to identify the fault and its development over time. The proposed scheme has been used in a real system and the results have confirmed that the proposed method can correctly identify the fault and islanding site.
|Number of pages||5|
|Publication status||Published - 21 Jul 2013|
|Event||IEEE Power & Energy Society General Meeting, 2013 (PES 13) - Vancouver Convention Centre, Vancouver, Canada|
Duration: 21 Jul 2013 → 25 Jul 2013
|Conference||IEEE Power & Energy Society General Meeting, 2013 (PES 13)|
|Period||21/07/2013 → 25/07/2013|