Microgrids (MGs) are capable to work at different operation modes, namely grid-connected or islanded, which make a significant change in the network fault current level. These changes may lead to problems and should be detected fast to do the proper protection actions accordingly and prevent blackouts. Moreover, some island detection methods suffer from the drawbacks of high computation burden and time-consuming procedure of training data to detect the islanded mode. For this purpose, in this paper, a faster and less computation burden island detection scheme without the need for training data is proposed which detects the islanded mode by analyzing the fault current data obtained from a continuous sampling using the phasor measurement unit (PMU). The sampled data are utilized in the fuzzy c-means (FCM) clustering to determine the network operation mode. The proposed scheme works in two phases. In the offline phase, the root mean square (RMS) of the current amplitude for islanded mode is determined, and in the online phase, the center of the measured data is compared to the RMS value to detect the MG operation mode at a decision making procedure. It is proved that the proposed island detection scheme is an applicable technique for detecting the islanded mode in MGs.

In this paper, a comprehensive statistics-based review of islanding detection methods (IDMs) in microgrids (MGs) is presented. Islanding detection is the situation of isolating the MG from the main grid whether programmed as a result of load managing purposes or un-programmed due to the occurrence of faults. Islanding detection is a vital issue in MG's analyses due to the prevention of subsequent protection problems in the power system. In other words, when the MG's operation mode changes, the current passing through the protective devices changes subsequently and the protection system should be able to adapt the new settings to the protective devices. So, IDMs are vital for electrical engineers to overcome the abovementioned protection issue. This review paper surveys the existing literature in IDMs by concentration on total publications, type of publications (journal, conference paper, or book), five authors with the highest number of publications (including the affiliations), and five most published sources. Also, the five most cited publications and state-of-the-art IDMs are investigated in detail, utilizing some known and novel categorizations. This paper will be useful for the MG's researchers to know the most desirable IDMs, especially in recent years, and provides an insightful overview for future studies.

Microgrid (MG) is a system of production and distribution of electrical energy that can operate both in grid-connected and islanded modes. This capability leads to significant variations in the fault current level. Moreover, dynamic changes corresponding to the line outage contingencies or outages of the distributed generations (DGs) that are implemented for local generation in the MGs lead to the changes in the fault current level. These changes in the fault current level make some miscoordination between the overcurrent relays (OCRs) in the conventional protection schemes. To overcome this drawback, there is a need for an adaptive protection scheme that can adapt to both operational and dynamic changes and takes effective protection decisions accordingly. This paper first presents a statistic-based review of MG and its protection including total publications, type of publications, the ten most researchers, and the ten most sources. Finally, comprehensive remarks of the 30 most cited papers related to adaptive protection of MG are presented. This paper will help the researchers of the MG protection to learn the most desirable techniques and the concentration of studies in adaptive protection of MGs for future works.

<span>Operational modes and topological changes affect power flow in the power systems. As a result, a broad spectrum of protection issues may happen in the power system. So, both the operational and topological changes should be detected fast to prevent blackouts. On the other hand, the existing detection schemes are complex in analyzing and implementation. Therefore, there is a need for an online scheme to identify the network's topology and operation mode simultaneously without complex computations and additional communication infrastructures. To this end, a comprehensive scheme is proposed in which the changes are detected by analyzing the power flow obtained from the network. For this purpose, line outage contingencies and operation modes are defined in rules to be used in a fuzzy inference system (FIS) as a decision-making tool. The proposed scheme can be implemented on existing lines as a communication infrastructure and determines the network’s status in an online manner. Also, in comparison to the existing schemes, the proposed scheme reduces the complexity and the computational burden. The proposed scheme is implemented on IEEE 8-bus system and the results proved its efficiency.</span>