A Novel Islanding Detection Method for Inverter-Based Distributed Generation Systems

Distributed generators (DGs) require detection of islanding condition due to personnel safety hazards and equipment damages. Anti-islanding methods are divided into passive and active methods. The passive methods are based on measurement of the natural effects of islanding. The active methods use the effects by intentional transients or harmonics. When the power generated by the DG matches power consumption by load, passive methods fail due to small natural effect of islanding. Therefore, the passive methods have a non-detection zone (NDZ). The active methods can reduce the NDZ size. But these methods reduce the power quality of the grid. In this paper, a novel anti-islanding method (AIM) is proposed. The single phase DG using the proposed AIM injects output current included a little harmonic current into the grid and monitors the harmonic component of voltage at the point of common coupling (PCC) by using Goertzel algorithm. The Goertzel algorithm is a kind of discrete Fourier transform (DFT). It extracts magnitude and phase of the desired frequency from the input signal, with minimum computation. The proposed islanding detection algorithm does not only have NDZ but also bad effect on the power quality of the grid due to injecting harmonic components qualified the interconnection standard. The proposed islanding detection method (IDM) is verified by the PSIM simulations and the experimental results.

Background: The growth of renewable energy sources is increasing in the world to meet the energy consumption demand. The major problem after the integration of renewable sources is islanding. The islanding is not safe for equipment and customers. As per Distributed Generation (DG) interconnection standards, it should be detected within 2 seconds. Objective: This paper presents the review of various islanding detection methods for increasing the stability of islanded DG. This will help future researchers for selecting the best islanding detection method with zero NDZ. Methods & Results: The islanding detection methods are classified as local and remote techniques. The local techniques are again classified as active, passive and hybrid methods. Each method is presented with their islanding detection time, power quality issues, Non Detection Zone (NDZ), advantages and disadvantages. Conclusion: The fuzzy based artificial intelligence with Particle Swarm Optimization (PSO) passive methods have been reduced the NDZ to zero and increase the stability of DG without degrading the power quality as active and passive methods.

Multi grid-connected inverters islanding detection methods include two categories: passive islanding detection and active islanding detection. Firstly, an active islanding detection method based on negative sequence current disturbance is analyzed. Aiming at the shortcomings of this method, a novel passive islanding detection method is proposed in this paper. The proposed islanding detection method uses wavelet transform to extract signal features, and then according to the extracted signal features adopts the neural network to judge whether or not the islanding occurs. The simulation results show that the passive multi grid-connected inverters islanding detection method has good islanding detection performance, and does not affect the stability and power quality of the system.

Grid converters are the key player in renewable energy integration. The high penetration of renewable energy systems is calling for new more stringent grid requirements. As a consequence, the grid converters should be able to exhibit advanced functions like: dynamic control of active and reactive power, operation within a wide range of voltage and frequency, voltage ride-through capability, reactive current injection during faults, grid services support. This book explains the topologies, modulation and control of grid converters for both photovoltaic and wind power applications. In addition to power electronics, this book focuses on the specific applications in photovoltaic wind power systems where grid condition is an essential factor. With a review of the most recent grid requirements for photovoltaic and wind power systems, the book discusses these other relevant issues: Modern grid inverter topologies for photovoltaic and wind turbines Islanding detection methods for photovoltaic systems Synchronization techniques based on second order generalized integrators (SOGI) Advanced synchronization techniques with robust operation under grid unbalance condition grid filter design and active damping techniques Power control under grid fault conditions, considering both positive and negative sequences Grid Converters for Photovoltaic and Wind Power Systems is intended as a coursebook for graduated students with a background in electrical engineering and also for professionals in the evolving renewable energy industry.

The number of DGs located at distribution site, which uses renewable energy sources, forms a Micro-grid system. The problem of using DG with the utility is unplanned islanding. This paper has focused on passive islanding detection method (IDM) which is easy for implementation, cheaper and proficient. The suggested method tried to eradicate the disadvantage of passive conventional IDM. Low impedance grid always immersed small deviation of inverter output in the grid-connected mode, but whenever the grid is disconnected (i.e. in islanding condition) this stability effect of the grid is absent, which is picked up for islanding detection in the proposed method. In this paper, voltage ripple-based passive IDM is evaluated and tested under various operating conditions. The proposed method is easily working on condition like generated power and load power are the same and it was found that technique is robust, without NDZ and can detect islanding within 0.3 sec. Also the proposed method is able to differentiate islanding and non-islanding scenarios, which is helpful to stop unnecessary malfunctioning of DGs.

This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT).

The quick detection of islanding in active distribution networks is the main challenge for power engineers. The late detection of islanding may have hazardous impacts on the power systems. Due to the advancement in photovoltaic (PV) technology and their eco-friendly nature, these systems are widely in demand. The islanding methods in the power system are classified into active, passive, remote, and hybrid. The passive methods depend on the measurement of electrical parameters such as voltage, frequency, and phase angle at the point of common coupling (PCC) during islanding condition. The purpose of this paper is to analyze the performance of different passive methods in 100 kW grid-connected PV array. This research paper compares over/under frequency, over/under voltage and rate of change of frequency (ROCOF)-based islanding detection methods (IDMs). The performance of these methods has been analyzed at different conditions. Computer simulations are performed using MATLAB/Simulink.

This article presents a Radial Basis Neural Network (RBNN) based islanding detection technique. 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. While passive schemes have a large non detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. 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. The proposed algorithm is compared with the widely used rate of change of frequency relays (ROCOF) and found working effectively in the situations where ROCOF fails. This approach utilizes rate of change of frequency at the target distributed generation location and fed to the radial basis neural network for intelligent islanding detection. Hence a better reliability is provided. This approach utilizes the artificial neural network (ANN) as a machine learning technology 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. Simulation studies showed that the RBNN-based algorithm detects islanding situation accurate than other islanding detection algorithms. Moreover, for those regions which are in need of a better visualization, the proposed approach would serve as an efficient aid such that the mains power disconnection can be better distinguished

At present, the commonly used active and passive islanding detection methods have their own shortcomings, and the islanding detection effect is difficult to meet the requirements. Therefore, a new detection method based on wavelet signal processing and artificial intelligence to identify islanding is proposed in this paper. In this method, the feature quantities required for islanding detection are obtained by wavelet transform and signal processing, and then the feature quantities are identified by neural network to determine whether the islanding is generated in distributed generation system. Wavelet transformation has a strong ability of signal feature extraction, while the neural network has strong learning and identification abilities, the combination of the both is beneficial to improve the success rate of islanding detection. Simulation verification shows that the new islanding detection method proposed in this paper can detect islanding quickly and accurately, and the performance of islanding detection has been significantly improved.

The existing passive methods for islanding detection are mainly based on the detection of voltage and frequency deviation after islanding, using protections such as voltage vector shift (VVS) and rate of change of frequency (ROCOF). Although there are reported issues with these passive methods such as inherent non-detection zones and nuisance trips, utilities prefer the passive methods due to the low cost and simplicity of deployment. In this paper, one composite passive islanding detection method is presented. It tracks the voltage phase angle, the system frequency, and ROCOF every power cycle. If three phase voltage vectors shift in the same direction and the rotated angle values are balanced, the calculation of the accumulated phase angle drift (PAD) will be initiated. This calculation continues until the ROCOF measurement is below the ROCOF setting threshold. If the accumulated phase angle drift reaches the set angle threshold, the condition for islanding is claimed. The performance of this composite method is verified under different scenarios based on Matlab Simscape multidomain physical systems and practical waveforms recorded from sites. Although there are still non-detection zones, this composite PAD solution has better sensitivity than existing VVS and ROCOF methods and is stable under external system faults.

The non-detection zone is a concept used to evaluate anti-islanding detection methods. The non-detection zone is defined as the loading condition for which an islanding detection method would fail to operate in a timely manner, and it is represented in terms of the load parameters. This article proposes a new three-dimensional non-detection zone representation for quantifying the effectiveness of frequency drift islanding detection methods. The proposed non-detection zone model is represented in terms of active and reactive power mismatch and load quality factor. Various two-dimensional non-detection zone models proposed in the literature are analyzed to highlight the limitations of each model. The analysis is conducted on three different islanding detection methods, including over-frequency protection/under frequency protection, active frequency drift, and Sandia frequency shift methods. The analytical model of the two dimensional non-detection zone representations is presented, and each model is validated through simulation results. The results show that representing the non-detection zone in a two-dimensional space is not sufficient to accurately determine all non-detectable loading conditions. The proposed three-dimensional non-detection zone representation is capable of modeling all possible loading conditions and provides a better approach for assessing islanding detection methods with resistance-inductance-capacitance loads.

In this paper, a new islanding detection method for inverter-based distributed generator (DG) is proposed, which is based on voltage amplitude variation. The proposed method can detect islanding with zero non-detection zone (NDZ), negligible consequence on power quality and simple performance. A new formula is embedded in the active power reference equation to deviate and accelerate the point of common coupling (PCC) voltage when islanding occurs. Therefore, a passive under/over voltage relay will be sufficient to detect islanding within the voltage permissible limit. The main benefit of the presented method is its independency from the load parameters such as loading quality factor. The proposed method is modelled with computer-aided SIMULINK/MATLAB software. The presentation of the proposed method is considered for a DG system with both unity and non-unity power factors. The performance is confirmed for different loading quality factors. Furthermore, it is also validated the proposed islanding detection method under imbalance loading.

Islanding in a gird connected inverter of wind power generation system may give a bad effect on equipments or yield safety hazards on grid so it should be detected rapidly and exactly. Passive methods are simple to detect islanding by monitoring parameters of system but it has non detection zone (NDZ). Active methods are more effective to detect islanding by injecting small disturbance into output of utility interactive inverter. This paper proposes a novel hybrid anti-islanding detection method, which combines the conventional passive over/under voltage and over/under frequency (OUV-OUF) method with a new active harmonic injection method. In the proposed scheme, the active methods can be used effectively to overcome the problem caused by the NDZ. When NDZ does not exist, the passive methods can detect the islanding rapidly. The effectiveness of the proposed scheme is proved through comparative simulation results.

One of the facing problems in distributed generation is being unintentionally islanded which the detection of this phenomenon is of great importance. Common methods are active and passive islanding detection. These two methods are based on changing in parameters such as frequency, voltage and current harmonics. If, after the islanding occur, this changes are revealing and visible, islanding phenomenon is demonstrated which is detected by passive methods. If the generated power of inverter is equal to local loads consumption and assuming of the generated reactive power of grid connected inverter equal to zero, it should be detected by active methods but these two methods have some challenges such as reduction in power quality or wide Non Detection Zone (NDZ). In this paper, in proposed method, change of a new parameter will be studied for islanding detection diagnosis. With the difference that the studied system is a three phase system and unbalanced load is studied which is more consistent to reality. Because of small changes in parameters, we have to find the right approach toward active methods. Generally there are two views about the islanding performance. At first view, this phenomenon is seems negatively but in fact this is an opportunity. The first view suggests that all generators in the island should bring out of grid within a maximum of two seconds. In this view the concept of anti-islanding protection is proposed to tackle the task of creating such islands. The second view expresses the concept of micro grid. In this case as far as possible, power required by Inner Island loads were provided by distributed generators. The studied system was similar to standard IEEE-1547 and UL-1741. With the difference that we used three phase and local loads are assumed unbalanced. Conventional active detection methods are not able to identify the island with the aim to help keep it stable. They usually try to bring out the electrical parameters such as voltage and frequency from nominal limits. So in micro grids the island should be diagnosed using passive or remote techniques. Note that detection time of 2 seconds which is referred to on standards is not good and the detection time must be lower than this value. However, the proposed method that is one of the active detection methods is capable for use in micro grids. Simulation results using PSIM software on standard network shows the effectiveness of the proposed method. Keywords: Islanding, Unbalanced Loads, dq-frame, Phase Locked Loop (PLL), Non Detection Zone (NDZ), Micro-grid.

The increased requirement for clean, cost effective and uninterrupted electricity has led to the incorporation of microgrid including distributed generation (DG) units. One of the major issue with DG interconnection is islanding detection. This paper presents the comparative assessment report of islanding detection techniques on the basis of their non detection zone (NDZ) and detection time. A comprehensive table comparing the different available islanding detection methods is also presented.