Islanding detection of distributed generations (DGs) is one of the most important aspects of interconnecting DGs to the distribution system. Islanding detection techniques can generally be classified as remote methods, which are associated with islanding detection on the utility sides, and local methods, which are associated with islanding detection on the DG side. This paper presents a survey of various islanding detection techniques and their advantages and disadvantages. The paper focused on islanding detection using a conventional and intelligent technique. A summary table that compares and contrasts the existing methods is also presented.

A review of islanding detection techniques for renewable distributed generation systems

High impedance fault detection: A review

A comprehensive study on different types of faults and detection techniques for solar photovoltaic system

This article proposes a new integrated diagnostic system for islanding detection by means of a neuro-fuzzy approach. Islanding detection and prevention is a mandatory requirement for grid-connected distributed generation DG systems. Several methods based on passive and active detection scheme have been proposed. Although passive schemes have a large non-detection zone NDZ, concern has been raised on active method due to its degrading power-quality effect. Reliably detecting this condition is regarded by many as an ongoing challenge as existing methods are not entirely satisfactory. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. In addition, this technique can also overcome the problem of setting the detection thresholds inherent in the existing techniques. In this study, we propose to use a hybrid intelligent system called ANFIS the adaptive neuro-fuzzy inference system for islanding detection. This approach utilizes rate of change of frequency ROCOF at the target DG location and used as the input sets for a neuro-fuzzy inference system for intelligent islanding detection. This approach utilizes the ANFIS as a machine learning technology and fuzzy clustering for processing and analyzing the large data sets provided from network simulations using MATLAB software. To validate the feasibility of this approach, the method has been validated through several conditions and different loading, switching operation, and network conditions. The proposed algorithm is compared with the widely used ROCOF relays and found working effectively in the situations where ROCOF fails. Simulation studies showed that the ANFIS-based algorithm detects islanding situation accurate than other islanding detection algorithms. © 2014 Wiley Periodicals, Inc. Complexity 21: 10-20, 2015

An adaptive neuro-fuzzy inference system for islanding detection in wind turbine as distributed generation

Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review

Wavelet transform method for islanding detection of wind turbines

During a power swing, currents and voltages behave such as a fault. Therefore, Power swing blocking function in distance relays is necessary to discriminate between a power swing and a fault. Otherwise power swings can be considered as a fault and causes relay trip. The main problem happens when during power sings a fault occurs. In this case, distance relays should be unblocked. In this paper, a new method based on the DC component of fault currents will be proposed to detect a fault during power swing blocking. The proposed method can detect single-phase to ground, two-phase to ground and three-phase fault. Applying the new method on a sample network reveals the features of the method.

A new method for fault detection during power swing in distance protection

A novel fault detection method for VSC-HVDC transmission system of offshore wind farm

The high impedance fault detection in power system is one of the hard works and if the fault does not clear then the power system may get into damage. In this paper a new method for high impedance fault detection is proposed. The proposed method is based on the chaotic and doffing function. The paper will propose the appropriate formula and the setting parameters. The method is applied on a sample distribution network and the simulation results show that the new method properly works.

New high impedance fault detection

This paper presents a new structure for a variable high speed and variable speed wind turbine based on a 12/8 switched reluctance generator (SRG). SR machines have a robust and simple structure because they have no windings or permanent magnets on the rotor, so they are capable of working at high speed applications and rough conditions. A SRG can be used as a reliable stand-alone generator due to several reasons such as high power density, low maintenance, high robustness, and high efficiency. In this paper, basic equations of two operation modes of SRG are extracted. The simulation results of the output waveforms of SRG used as high speed stand-alone generator are presented. The impacts of variations in wind speed are discussed.

H. Kazemi Karegar

Papers

Wavelet transform method for islanding detection of wind turbines

A new method for fault detection during power swing in distance protection

A novel fault detection method for VSC-HVDC transmission system of offshore wind farm

New high impedance fault detection

New structure for high speed and variable speed wind turbine based switched reluctance generator