A Multistage Passive Islanding Detection Method for Synchronous-Based Distributed Generation

A novel, multistage approach to passive islanding detection is presented which uses a decision-tree-like classification algorithm. The novelty of the proposed method is centered on the way in which features are passed to subsequent stages of the decision tree (DT). A traditional DT uses a single feature set while in the modified algorithm, feature sets extracted using different sized time windows are passed to successive stages of the tree. This provides two important advantages: (i) cases which can be easily determined as either islanding or non-islanding events are flagged as soon as possible without waiting for the full feature set to become available (ii) because the algorithm allows for the use of different sized time windows, features are analyzed in time-scales which fit their natural patterns of temporal evolution. The proposed classifier is trained and tested using a database of feature vectors obtained via PSCAD/EMTDC simulations (based on an IEEE 34-bus distribution system) which were carefully designed to reflect a variety of commonly encountered events and load profiles. As mentioned, one of the key requirements for the proposed algorithm was that “easy” cases should be flagged as soon as possible; this property was confirmed by the observation that most events (≈79%) were detected within 10-20ms, while at the same time retaining a very high detection rate over all cases (> 99%).