An intelligent Island detection scheme to enhance grid resilience

The importance of strengthening grid resilience has grown with the increase in environmental destruction and modern power grid complexity, as a consequence of power outages inflicted by human intrusion and extreme weather events. Micro-grids (MGs) have proven to be a viable alternative in such circumstances. However, these occurrences are highly unpredictable, resulting in unintended islands of MGs with negative consequences. As a response, alerting its distributed generations about unintended island is indeed a crucial issue for enhancing grid resilience with MG. Therefore, it is essential to develop a technique for the efficient and accurate detection of unintended islands. There has been an increase in the use of micro-phasor measurement units (µ-PMUs) in MG. In the perspective of this, using an efficient µ-PMU, the research provides a method for finding unintended islands in a MG. The µ-PMU analyses the solar generator bus voltage and analyzes it with symmetrical components for island identification. This study introduces a µ-PMU based Fortescue-transform and random forest algorithm method for rapid detection of unintended islanding in distribution generation system. The approach monitors voltage phasor of zero and negative sequence, calculating angular sum over time to distinguish islanding event from other disturbance. Using Matlab/Simulink, the proposed method is evaluated on the IEEE-34 node distribution network. Multiple simulations provide validation for the method’s resilient performance. The methodology proposed has a detection time of 20 ms.