A Statistical Features Based Generic Passive Islanding Detection Scheme for IIDGs System

This paper proposes a new passive Islanding detection approach for the Inverter Interfaced Distributed Generators (IIDGs) operating under different control modes. First, a novel index is formulated using Root Mean Square (RMS) value of the voltage and the frequency information, acquired at the Point of Common Coupling (PCC) of the target DG. The index is then post-processed by estimating the number of peaks and valleys $(N_{p_{k}-v})$ in a cycle using the sliding window concept, which indicates the occurrence of an event. Finally, the nature of the event, i.e., Islanding or non-Islanding, is decided by exploiting the two statistical features viz., Square of RMS $(S_{RMS})$ of $N_{p_{k}-v}$ and Average Crest Factor $(ACF^{m})$ of the proposed index. The performance of the proposed method (P-IDM) is demonstrated through comprehensive studies in PSCAD/EMTDC for the single-bus and IEEE 34-bus Active Distribution System (ADS). Also, the real-time validation is performed for the IEEE 34-bus using Controller Hardware-in-the-Loop (CHIL) setup comprising of Real-Time Digital Simulator (RTDS) and dSPACE1104. The simulation and hardware results for different test systems indicate that the proposed scheme, being generic in nature, sustains its efficacy under various interface controls of IIDGs. Finally, a comparative assessment with the other existing Signal Processing (SP) based passive methodologies shows the supremacy of the proposed method in terms of accuracy and faster detection.