A Net Energy Meter-Based Approach for Islanding Detection in Modern Distribution Systems

The era of smart grid has provided unprecedented opportunities, which has taken the power industry to a new level assuring better reliability, continuity and productivity. However, the grid system has to face challenging uncertainties due to faults, voltage dip, islanding, etc. Islanding can be defined as a situation during which distributed generation (DG) continue to feed some portion of loads even after being disconnected from the main grid. Island situations can be dangerous for the utility workers and users end equipments. Net energy meter (NEM) has the ability to record flow of energy in two directions. To feed the household loads, consumer utilizes power from two sources i.e. from the grid and different DGs. If there is a surplus power 360generation by DGs, the excess power will be fed back to the grid through a NEM. To deal islanding events with NEM, this chapter recommends an advance technique of detecting islanding for doubly-fed induction generator (DFIG) wind turbines based microgrid. Walsh Hadamard transform (WHT) is used as the signal processing tool to generate the WHT coefficients of the signals derived from net energy meter (NEM) and artificial neural network (ANN) has been employed for the examination of these coefficients and classification/detection of islanding events. The results obtained for various islanding and non-islanding scenarios show that the presented method is faster and effective. The simulation is performed in MATLAB/SIMULINK environment.