Standalone condition diagnosing of fuel cell in microgrid composed of wind turbine/fuel cell/combined heat & power using Variational Mode Decomposition analysis model

With increasing load in the power system, several new energy resources such as Fuel Cell (FC) have been added into the systems which increased the systems complexity and uncertainty. Unwanted islanding is one of the main problems for this generation. This article presents a novel technique for fuel cell system islanding detection using Variational Mode Decomposition and Radial Bases Function pattern learning technique. In this technique the state changes of Intrinsic Mode Functions energy of THD signals in two-dimensional mode is utilized as input data of relay. An optimal signal selection model is applied to the proposed relay in order to Non-Detection Zone and fails detection reducing. The best signal selection is introduces based on mean square value between islanding and non-islanding conditions. Also, by considering Optimal Radial Bases Function model for the proposed relay as a pattern recognizing and weighing it using shark smell optimization, this technique has overcome the threshold selection problem. This relay is applied to FC system in a microgrid system contains various types of DGs. Many islanding and non-islanding situation in various operation conditions in the studied microgrid are simulated. The results of simulation results are show that the proposed relay is suitable for microgrid application. Negligible NDZ, high detection time, zero fail detection and low cost of this relay are the main advantages of the proposed technique.