Islanding Fault Research Articles

Islanding Fault Detection in Microgrids—A Survey

This paper provides an overview of islanding fault detection in microgrids. Islanding fault is a condition in which the microgrid gets disconnected from the microgrid unintentionally due to any fault in the utility grid. This paper surveys the extensive literature concerning the development of islanding fault detection techniques which can be classified into remote and local techniques, where the local techniques can be further classified as passive, active, and hybrid. Various detection methods in each class are studied, and advantages and disadvantages of each method are discussed. A comprehensive list of references is used to conduct this survey, and opportunities and directions for future research are highlighted.

Set-Membership Global Estimation of Networked Systems.

This article is concerned with set-membership global estimation for a networked system under unknown-but-bounded process and measurement noises. First, a group of local set-membership estimators is deployed to obtain the local ellipsoidal estimate of the true system state. Each estimator is capable of communicating with its neighbors within its communication range. Second, a global estimation approach is proposed which generates a trace-maximal ellipsoid within the intersection of all the local estimation sets with an aim to improve the difference of the local estimate at each time instant. Sufficient conditions for providing a global estimate under both complete and incomplete measurement transmissions are derived. Third, as an application, a modified distributed photovoltaic grid-connected generation system is provided to verify the effectiveness of the developed set-membership global estimation approach. Furthermore, an islanding fault detection scheme is derived based on the calculated global ellipsoidal estimate. Finally, simulation verification of the obtained theoretical results on the distributed generation system is presented.

An Islanding Fault Detection Method with CFDF-SVM Based RPV Approach under Pseudo Islanding Phenomenon

Islanding detection is an important issue in distributed generations (DGs) systems. Therefore, anti-islanding protection is a critical concern. A novel reactive power variation (RPV) islanding detection method based on correlation function data fusion and support vector machine (CFDF-SVM) approach is presented to reduce the non-detection zone (NDZ) and avoid the false detection caused by pseudo islanding phenomenon (PIP). The feature data sets (frequency, injected reactive power, fundamental and third harmonics of point of common coupling (PCC) voltage and current) are acquired by Fourier transform and fused by CFDF approach. After that, the fused data sets are classified into two categories by an SVM approach: islanding and non-islanding. In addition, the proposed approach is based on the active intermittent RPV method which reduced the NDZ fundamentally. Compared with the traditional RPV method, the proposed method could detect islanding event accurately, and the false detection rate caused by PIP is significantly reduced. Then a single-phase-inverter is built by Simulink, the detection results have proved the effectiveness of the proposed method.

Event-Based Networked Islanding Detection for Distributed Solar PV Generation Systems

This paper proposes an event-based networked set-membership filtering method to detect islanding fault for distributed grid-connected solar photovoltaic generation systems. The method enables each set-membership filter to offer an ellipsoidal estimation set, which is used to judge whether or not the islanding fault happens. When islanding fault happens, the intersection of the ellipsoids is empty, and when islanding fault is free, the intersection of the ellipsoids is nonempty. In the filtering scheme, a novel event-triggered mechanism is proposed to reduce the transmission frequency for saving the communication resources. The condition of the existence of the set-membership algorithm is derived by a time-varying convex optimization approach. A simulation experiment and a comparative experiment are provided using Sim-Power-Systems implementation based on a 2-kW single-phase grid-connected power generation system to illustrate the effectiveness of the proposed method for the detection of the islanding fault and the reduction of the resource consumption, respectively.

Time-Frequency Analysis based Approach to Islanding Detection in Micro-grid System

This paper presents a novel technique based on time-frequency analysis to detect the islanding conditions in distribution network with the presence of multiple distributed generations (DGs).Various islanding and non-islanding fault conditions such as capacitor switching, load rejection and line to line fault etc., are analyzed through negative sequence decomposition technique. Feature extraction has been carried out by two time–frequency analysis techniques based on wavelet transform (WT) and S-Transform (ST). For the detection of various disturbances the energy and standard deviation (SD) features of signals are estimated by wavelet transform coefficient and S-transform matrix. Furthermore, based on the estimated features the artificial neural network (ANN) and support vector machine (SVM) are used as a classifier to classify the islanding and non-islanding events. For showing the effectiveness of the proposed technique to detect islanding conditions under a wide range of operating environment, some simulated results are presented.

An Active Islanding Detection Method for Grid-Connected Renewable Energy Generation System

This study proposes an active islanding detection method for use of grid-connected inverter of renewable energy generation system (REGS). With a digital signal processor (DSP) integrated, the proposed method is capable of detecting the islanding fault of grid-connected inverters of REGS during the variable load conditions. To verify the effectiveness of the proposed method, the method was tested on a practical inverter of REGS, the field practical operations of the proposed method were studied in accordance with the conditions for the different loads and fault types. Test results are presented which show that the new proposed method is reliable, economical and easy for implementation.

A novel islanding fault detection for distributed generation systems

SUMMARYThis paper proposes a novel islanding fault detection method for distributed generation systems. Islanding fault detection of distributed generation systems in microgrids and smart grids is an essential security technology. The existing methods for islanding fault detection can be classified as passive methods (such as under/over voltage detection, under/over frequency detection, and voltage phase jump detection, based on natural effects of islanding) and active methods (impedance measurement, slip mode frequency shift, Sandia frequency shift and so on). Once the power consumed by a local load matches the power generated by a local inverter, the islanding phenomenon will be not obvious, and traditional passive methods may fail. In contrast, the active methods can overcome this disadvantage. However, active methods create extra disturbances that may degrade the quality of power generated by the inverter. By reducing the harmonics of the inverter output, coupled with the use of a novel filtering method, the proposed approach can be achieved without additional disturbance and does no nondetection zone islanding detection. In this paper, current harmonic compensation is applied to inverter control to minimize the inverter output harmonics, highlighting on the grid harmonics. Set‐membership filter is developed to estimate the voltage harmonics. Islanding condition is detected by the changes of the specific order harmonics. The effectiveness of the proposed method is demonstrated by simulations. A Kalman filter contrast experiment is presented to confirm that the set‐membership filter can more effectively detect islanding. Copyright © 2013 John Wiley & Sons, Ltd.