Data‐mining‐based intelligent anti‐islanding protection relay for distributed generations

A data‐mining‐based intelligent anti‐islanding detection scheme for distributed generation (DG) protection has been presented. The process starts at deriving highly involved features using discrete Fourier transform‐based pre‐processor at the DG end. The features derived include both positive and negative sequence quantities and related features. Once the features are retrieved, the decision tree is trained to build a data‐mining model for identifying the islanding events from non‐islanding situations, including disturbances close to islanding conditions. The proposed anti‐islanding relay is extensively tested on simulation model and provides encouraging results considering wide variations in operating conditions. Further, the validation is extended on real‐time digital simulator module to test the efficacy of the proposed anti‐islanding relay. The test results indicate that the proposed anti‐islanding relay can reliably detect islanding conditions while meeting the speed criteria.