An innovative hybrid method for islanding detection using fuzzy classifier for different circumstances including NDZ

Abstract

Distributed energy resources (DERs) are an alternative to conventional fossil fuel-based energy resources for a pollution-free operation. But the integration of these DERs to the main grid comes with certain challenges, out of which unintentional islanding detection is of prior importance. A lot of techniques have been used for detecting islanding, among these techniques, passive and active. Passive islanding detection methods have drawbacks in the form of the existence of large non-detection zones whereas active detection methods have devastating effects on power quality. To overcome these drawbacks, a proposed hybrid passive-active systematic methodology based on a smart classifier that decides to use an active method instead of a passive one; is presented. The simulation results confirm that the proposed scheme is accurate, robust, fast, simple to implement for inverter-based DGs, and is able enough to perform effective and rapid detection of islanding in all the circumstances for the chosen system model without degrading power quality. The proposed scheme was simulated using the MATLAB/Simulink platform, and the results reflect its potential with a comparative study.

Keywords

• Distributed generation
• Fuzzy classifier
• Grid faults
• Islanding detection
• Non-detection zone