Islanding detection of inverter-based distributed generation

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.

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

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.

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.

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.

This paper provides an analytical survey of the islanding detection techniques for the distributed generation systems. Islanding phenomena on takes place when the power supply from the main utility is intermittent due to numerous reasons, but the distributed generation keeps supplying power into the distribution networks. Islanding can be dangerous to workers and electrical equipment, even the power grid. Therefore, islanding detection is the priority among priorities. Islanding detection is a precondition of two working modes switching for distributed generation. In this paper, a detailed description followed by the classification of the islanding detection techniques has been made based on features, such as detection time, size of non-detection zone, power quality disturbances, system cost and operation under multiple distributed generation units. The merits and demerits of islanding detection methods are analyzed and summarized in this paper. In this manner, the greatest detection outcome can be achieved by exploiting the merits of each method. This paper is aimed to serve as a convenient reference and guidance value for deciding the islanding detection method for future islanding users in distributed generation system.

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

Nowadays, distributed generation (DG) has become an indispensable part for meeting the growing power demand in electrical power generation and distribution. However, one of the drawbacks of DG is unintentional islanding phenomena, which has become a safety issue for both human and equipment connected to the system. To prevent this hazardous condition, according to IEEE 1547 standards, this islanding condition must be detected within 2 s. This paper proposed an approach to develop a hybrid islanding detection method (IDM) to prevent the damages caused by this islanding condition. The proposed hybrid IDM is a combination of three different IDMs, two passive and one active; that is, rate of change of active power (ROCOAP) and rate of change of reactive power (ROCORP) are passive IDMs where load connecting strategy (LCS) is active. To differentiate islanding conditions with similar occurrences, different case studies are taken into account with photovoltaic (PV) and synchronous generator (SG) working as distributed generators on PSCAD/EMTDC platform. The simulation results confirm that proposed IDM is more favorable compared to other IDMs due to simplicity and fast islanding detection time when its performance is tested on the 11‐kV Malaysian distribution system for various cases.

This paper proposes an autonomous unified var controller to address the system voltage issues and unintentional islanding problems associated with distributed photovoltaic (PV) generation systems. The proposed controller features the integration of both voltage regulation (VR) and islanding detection (ID) functions in a PV inverter based on reactive power control. Compared with the individual VR or ID methods, the function integration exhibits several advantages in high PV penetration applications: 1) fast VR due to the autonomous control; 2) enhanced system reliability because of the capability to distinguish between temporary grid disturbances and islanding events; 3) negligible nondetection zone (NDZ) and no adverse impact on system power quality for ID; and 4) no interferences among multiple PV systems during ID. As the VR and ID functions are integrated in one controller, the controller is designed to fulfill the requirement of VR dynamic performance and ensure small ID NDZ simultaneously. The interaction among multiple PV systems during VR is also considered in the design procedure. Finally, the feasibility of the proposed controller and the controller design method is validated with simulation using a real-time digital simulator and a power hardware-in-the-loop testbed.

ABSTRACTImproved efficiency, enhanced integration with distributed generations (DGs), and the proliferation of DC loads in power systems have driven a surge in the adoption of DC microgrids (DCMGs). However, unintentional islanding poses a significant threat to these microgrids, necessitating robust islanding detection techniques to safeguard personnel, equipment and system stability. This paper proposes two novel passive islanding detection methods for DCMGs, explicitly addressing the non‐detection zone (NDZ). The first proposed method involves collecting voltage samples at the DG terminals and computing their empirical mode decomposition (EMD). Subsequently, intrinsic mode functions (IMFs) are extracted, and the energy in each window is calculated to establish a diagnosis. To effectively distinguish islanding from other disturbances and faults, various scenarios are investigated. The second method is predicated on ensemble empirical mode decomposition (EEMD). Following the collection of voltage samples from DG terminals, white noise is introduced to these samples. The method subsequently extracts IMFs through averaging and quantifies the energy content within each window. The proposed methods are validated through simulations in Simulink/MATLAB. The obtained results demonstrate the methods’ effectiveness in achieving fast and accurate islanding detection.

Sandia frequency shift (SFS) islanding detection method is considered amongst the most efficient islanding detection methods that possesses small non-detection zone (NDZ) for inverter based distributed generation (DG). The NDZ of the SFS depends to a great extent on its design parameters. In this paper, the SFS parameters are determined through an instability criterion to guarantee negligible NDZ for the different loading conditions. The optimal SFS setting is calculated by setting the phase angle - frequency curve slope of the inverter to be greater than the slope of all expected island loads. A non-linear optimization program is formulated on GAMS to calculate the SFS parameters. The analytical results are verified through digital simulation on PSCAD/EMTDC.

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.

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.

In this paper, a passive neuro-wavelet based islanding detection technique for grid-connected inverter-based distributed generation was developed. The weight parameters of the neural network were optimized by intelligent water drop (IWD) to improve the capability of the proposed technique in the proposed problem. The proposed method utilizes and combines wavelet analysis and artificial neural network (ANN) to detect islanding. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem-free. Unintentional islanding is one of the encountered problems. Discrete wavelet transform (DWT) is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. In passive schemes with 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 simulation results from Matlab/Simulink shows that the proposed method has a small non-detection zone, and is capable of detecting islanding accurately within the minimum standard time.

An improved active islanding detection method for grid-connected solar inverters with a wide range of load conditions and reactive power