Abstract
In this paper, a new innovative type-2 fuzzy-based for microgrid (MG) islanding detection is proposed in the condition of uncertainties. Load and generation uncertainties are two main sources of uncertainties in microgrids (MGs). Regardless of the uncertainties, the results cannot be confirmed. The proposed controller detects islanding in the fastest time under different conditions, and the uncertainties in the system will not considerably affect the controller’s performance. The proposed method is simulated on the sample system and examined in different scenarios. Then, a comparison is made in different conditions and scenarios between the suggested method and some common methods that have been presented so far to demonstrate the ability of the proposed method for islanding detection.
Highlights
The MG islanding must be identified as soon as possible and appropriate control orders issued
It is assumed that the number of changes and the rate of change of frequency (ROCOF) for islanding are known, and in the proposed controller, the frequency is first sampled and compared with the reference frequency, the output of this comparison is amplified and its derivative is obtained
To investigate the effect of the type of power exchange between the system and the microgrid on frequency changes and islanding detection, we considered the system voltage angles in three different modes: 0 and ±12
Summary
The MG islanding must be identified as soon as possible and appropriate control orders issued. With the growth of intelligent methods, attention has been focused on using these methods to identify islanding cases Examples of such methods include the decisionmaking tree (DT) [32], support vector machine (SVM) [33], artificial neural network (ANN) [34], fuzzy logic control (FLC) [35], and adaptive neuro-fuzzy inference system (ANFIS) [36], which are used to categorize different conditions. Several me intelligent methods are unable to detect the islanding mode in a short time due to the complex logic behind them. A new innovative fuzzy based controller is proposed to determine the islanding mode in the event of system uncertainty.
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