Islanding Detection Research Articles

An optimal deep learning based Islanding power quality detection technique for distributed generation systems

Power quality disturbance (PQD) defines the presence of inconsistencies that occur in the usual wave shapes of voltage and current signals. Power quality is considered the main challenge for power industry with the increase in dynamic load and highly subtle electronic devices. Besides, the islanding events, particularly unintended islanding, grasp significant challenges and it needs to be identified at the early stage. Islanding is an anomalousstate in the power system, where the distributed generators (DGs) are placed on supplying electrical energy to the local load even after the shortage of the major grid. Therefore, it is essential to identify and differentiate the PQ events and islanding events in ensuring pollution-free power, equipment, and labor safety. With this motivation, this paper presents an automated optimal deep learning based islanding detection (AODL-ID) technique. The proposed AODL-ID technique involves three major stages namely decomposition, classification, and hyperparameter tuning. Firstly, an empirical mode decomposition (EMD) approach is utilized to decompose the basic signals from the polluted signals. In addition, bidirectional gated recurrent neural network (BiGRNN) technique is employed for the classification of islanding and non-islanding PQ events in the wind energy penetrated DG systems by means of features (Voltage and current (RMS, half-cycle, peak and fundamental) Frequency. Power Factor / Cos Phi. Power and energy (active, reactive, harmonic, apparent)). Since the hyperparameters play a significant role in overall classification performance, the hyperparameter tuning of the BiGRNN model takes place using chaotic crow search algorithm (CCSA). To examine the enhanced classification outcome of the AODL-ID technique, a set of experimental analyses is carried out and the outcomes are investigated interms of various evaluation metrics. The simulation outcomes highlighted the supremacy of the AODL-ID technique over the compared techniques.

Performance of a new hybrid approach for detection of islanding for inverter-based DGs

This paper proposes a new hybrid method for islanding detection and minimizes the Non-Detection Zone (NDZ), for an inverter-based grid-connected distributed generation (DG) system. The proposed hybrid method is an integration of the modified active Sandia Frequency Shift (SFS) method and the passive reactive power variation technique. The modified active SFS method is obtained by adaptive tuning of the gain parameter Ksfs, using the Adaptive Particle Swarm Optimization (APSO) technique. The proposed hybrid method produces a significant reduction of NDZ and is suitable for more accurate detection of islanding condition. The effect of NDZ for the proposed hybrid method has been derived analytically and the system performance has been assessed, under various power mismatch conditions for a DG-grid interface. The overall system performance has been found to be superior under the presence of constant power control strategy. The effect of frequency and voltage variations at the common coupling point during islanding have also been considered. Finally, the performance of the proposed method under the IEEE standard 1547 islanding test condition has been investigated for different load factors and load variations.

A Statistical Features Based Generic Passive Islanding Detection Scheme for IIDGs System

This paper proposes a new passive Islanding detection approach for the Inverter Interfaced Distributed Generators (IIDGs) operating under different control modes. First, a novel index is formulated using Root Mean Square (RMS) value of the voltage and the frequency information, acquired at the Point of Common Coupling (PCC) of the target DG. The index is then post-processed by estimating the number of peaks and valleys <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(N_{p_{k}-v})$</tex-math></inline-formula> in a cycle using the sliding window concept, which indicates the occurrence of an event. Finally, the nature of the event, i.e., Islanding or non-Islanding, is decided by exploiting the two statistical features <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">viz.,</i> Square of RMS <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(S_{RMS})$</tex-math></inline-formula> of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N_{p_{k}-v}$</tex-math></inline-formula> and Average Crest Factor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(ACF^{m})$</tex-math></inline-formula> of the proposed index. The performance of the proposed method (P-IDM) is demonstrated through comprehensive studies in PSCAD/EMTDC for the single-bus and IEEE 34-bus Active Distribution System (ADS). Also, the real-time validation is performed for the IEEE 34-bus using Controller Hardware-in-the-Loop (CHIL) setup comprising of Real-Time Digital Simulator (RTDS) and dSPACE1104. The simulation and hardware results for different test systems indicate that the proposed scheme, being generic in nature, sustains its efficacy under various interface controls of IIDGs. Finally, a comparative assessment with the other existing Signal Processing (SP) based passive methodologies shows the supremacy of the proposed method in terms of accuracy and faster detection.

Review on islanding detection methods for grid‐connected photovoltaic systems, existing limitations and future insights

The connection of renewable energy sources (RESs) to the distribution network has been rising at a steady pace over the past decades. The great penetration of RESs such as grid-connected photovoltaic system brings new technical challenges to the distribution networks such as unintentional islanding. Conceptually, this situation occurs when a portion of the network that has been isolated from the main grid remains energised by the embedded RESs. This unexpected scenario should be thereby identified effectively to avoid frequency and voltage deviations and their hazardous effects. The aim of this paper is to provide a comprehensive review on the recently developed islanding detection methods for grid-following/grid-connected photovoltaic system, analyse their existing limitations, and suggest possible future research implementations. In this context, an in-depth comparison is provided considering the main features used in islanding detection methods such as non-detection zone, detection time, implementation cost and complexity, and power quality degradation. Finally, the main technical requirements established by the current grid codes are recalled identifying potential multi-functional approaches to expand the current islanding detection capabilities.

A Hybrid Islanding Detection Method for One Cycle Controlled PV Inverter System

Features like phase locked loop free implementation, simple-structure, grid voltage sensor-less operation, and its feedback response make one cycle control (OCC) inverters suitable and cost-effective for small single-phase photovoltaic distributed generator units. The feedback nature of OCC makes passive islanding detection more effective in comparison with other control methods. A novel hybrid islanding detection method (IDM), which is suitable for OCC inverters, is proposed in this article. The hybridization is done in two levels and is aimed at reducing the nondetection zone of the existing feedback-based passive IDM. The passive first level defense, which is always present, is due to the feedback nature of OCC. When islanding is suspected, the active second level defense is initiated by injecting a short real power disturbance. This accelerates the feedback action and helps in timely detection of islanding. Unlike other active methods, the disturbance is injected only when an islanding condition is suspected. The induced disturbance in real power is momentary, and the inverter goes back to the normal operation under nonislanded conditions. Simulation and experimental studies are performed to verify the effectiveness of the proposed IDM.

A Novel Islanding Detection Technique Based on Positive-Feedback Negative Sequence Current Injection

This article proposes a new active anti-islanding technique to detect unintentional islanding with high speed and reliability. In grid-connected mode, the controller has no influence on the power system. When the grid is disconnected, the inverter injects negative sequence current in a positive feedback loop, and causes the output negative sequence voltage to increase to a threshold value that causes the inverter to stop operating. The proposed method is nonintrusive and does not cause disturbance to the system in grid-connected mode. The method is tested using PSCAD simulation software, and using controller hardware-in-the-loop (C-HIL) using the physical control board of the inverter. The inverter considered in this article is a photovoltaic inverter with 840-kW rated power. Optimization of the parameters of the proposed control, as well as small signal stability analysis in grid-connected mode are presented. Verification results show that the controller can detect unintentional islands and stop the inverter within 500 ms.

Analysis of Passive Islanding Detection Techniques for Double Line Fault in Three Phase Microgrid System

Microgrids are able to dispatch power to distribution systems with the advancement of power electronics-based inverters. As per IEEE-1547-2018 standards, Microgrid has to maintain voltage of 0.88 < V < 1.1 p.u (per unit) and frequency of 58.8< f_0 < 61.2 Hz and detect un-intentional faults in less than 2 seconds to bring Microgrid into islanding mode seamlessly. Unless these faults are detected and Microgrid is islanded, the system stability cannot be maintained and Microgrid cannot feed the connected loads. To detect these unsymmetrical faults, to bring the Microgrid to islanding mode and to be stable during non-islanding cases like loads switch on and throw off at Point of Common Coupling (PCC), a passive islanding detection method, Rate Of Change Of Voltage Phase Angle (ROCOVPA) is proposed. The methodology is simple. First, the voltage phase angle of generator bus and the grid is monitored. Then, absolute value is found and finally differentiated to get ROCOVPA and detect islanding. Also, this technique is compared with the widely used method of Rate Of Change Of Frequency (ROCOF) at different percentage active and reactive power mismatches. It also avoids nuisance tripping so that Microgrid's stability is maintained. This method is tested for un-symmetrical double line fault, for islanding cases and switch on or throw off, for non-islanding cases with linear and non-linear loads. In this method, the power quality is also not affected because of no perturbations during testing and the Non-Detection Zone (NDZ) is almost zero. The proposed method is verified by simulating islanding and non-islanding conditions in MATLAB/Simulink and by comparing with ROCOF method and found effective.

A new hybrid islanding detection method for mini hydro-based microgrids

This paper proposes a fast and reliable hybrid islanding detection method (IDM) for mini-hydro-based distributed generations (DGs) with zero non-detection zone (NDZ). The proposed IDM aims to tackle the islanding events caused by a self-excited induction generator (SEIG) when it is driven by a mini-hydro turbine system utilising the transient dynamic response of the governor for the first time. To achieve such a goal, it takes advantage of a two-stage process in which both passive and active techniques are combined. Thus, if the rate of change of frequency (ROCOF)-based threshold of the first stage is exceeded, the power reference of the mini-hydro unit is modified, implying a change in the turbine governor gate position. The mechanical torque applied to the prime mover is accordingly shifted to a new state so that both frequency and its derivative will exceed the established thresholds in the second stage in the islanding mode. Conversely, the effect of imposed disturbance is eminently negligible in the grid-connected mode since the frequency is strictly dictated by the main grid. The proposed IDM has been evaluated through numerous islanding and non-islanding case studies considering both single and multi-DG scenarios in MATLAB/Simulink. The outcomes highlight the outstanding performance of the proposed algorithm with zero NDZ and 473 ms average detection time, indicating the capability of the governor system as a reliable tool to identify islanding operations. The proposed technique does not degrade the power quality (PQ) of the grid, requires a low level of computational complexity and provides a high degree of reliability. Therefore, it is a robust and cost-effective solution for future microgrids with great penetration of mini-hydro units.© 2017 Elsevier Inc. All rights reserved.

An impedance identification-based islanding detection method for droop control inverters based on RDFT and positive–negative notch filters

Droop control inverters are widely used because of their plug-and-play characteristics, no need for communication, and adaptability to weak power grids. However, because of the difficulty of islanding detection, after the grid is restored, drooping control inverters may cause security problems. In order to address this issue, this paper proposes an islanding detection method for droop control inverters based on impedance identification. By injecting current disturbance into common coupling points (PCC), the impedance is identified by the current response, and then the islanding can be determined by the impedance change. On the one hand, a signal extraction method based on positive–negative notch filters is proposed to reduce the content and impact on the power quality of the disturbance injection. On the other hand, this paper uses a signal processing method based on recursive discrete Fourier transform (RDFT), which can effectively reduce the computational burden. Moreover, the proposed method can eliminate the non-detection zone of the island detection. The experimental results verify the effectiveness of the proposed method.

DTCDWT-SMOTE-XGBoost-Based Islanding Detection for Distributed Generation Systems: An Approach of Class-Imbalanced Issue

This article offers an islanding detection approach based on dual-tree complex discrete wavelet transform (DTCDWT) and extreme gradient boosting method (XGBoost). Initially, the DTCDWT is used to extract the feature vector from collected negative sequence voltage and current signals at the respective distributed energy resource ends. Afterward, the nonlinear synthetic minority oversampling technique (SMOTE)-based XGBoost is used to classify the islanding (I) and nonislanding (NI) events with the following characteristics: high accuracy, good sensitivity, and faster speed. Here, the SMOTE is used as an offline prefeature processing approach to reduce the unbalancing/uncertainty of “I” and “NI” classes and helps the intelligent classifier to impart a fair classification result. This scheme is found to be effective for the detection of I and NI conditions, satisfying the IEEE islanding detection standard. Additionally, the obtained simulation results are compared with other existing works to show its usefulness.

A simplified passive islanding detection technique based on susceptible power indice with zero NDZ

Distributed energy resources (DER’s) incorporation in power system brings economical, technical and environmental benefits. Besides these benefits, excess penetration of DER’s elevates technical concerns. Islanding detection is one of main issue and is essential for personnel safety and protection of equipment. This work introduces a passive islanding detection scheme based on phase angle of positive sequence voltage (PAOPSV). The PAOPSV was selected on the basis of rigorous investigation of 13 different indices. Comparative analysis demonstrates that PAOPSV has the best sensitivity and accuracy for islanding detection among all other parameters. An extensive case study considering worst-case scenarios is accomplished in order to check the working efficacy of the suggested scheme that easily discriminates islanding events from non-islanding events such as load switching, different fault types switching, capacitor and motor switching. The suggested scheme is simple with fast execution and easy to implement that is established on IEEE 1547 generic test system in MATLAB/SIMULINK environment. Islanding is detected within 0.10 s even with a zero non-detection zone.

An innovative hybrid method for islanding detection using fuzzy classifier for different circumstances including NDZ

Distributed energy resources (DERs) are an alternative to conventional fossil fuel-based energy resources for a pollution-free operation. But the integration of these DERs to the main grid comes with certain challenges, out of which unintentional islanding detection is of prior importance. A lot of techniques have been used for detecting islanding, among these techniques, passive and active. Passive islanding detection methods have drawbacks in the form of the existence of large non-detection zones whereas active detection methods have devastating effects on power quality. To overcome these drawbacks, a proposed hybrid passive-active systematic methodology based on a smart classifier that decides to use an active method instead of a passive one; is presented. The simulation results confirm that the proposed scheme is accurate, robust, fast, simple to implement for inverter-based DGs, and is able enough to perform effective and rapid detection of islanding in all the circumstances for the chosen system model without degrading power quality. The proposed scheme was simulated using the MATLAB/Simulink platform, and the results reflect its potential with a comparative study.

Detection and classification of islanding by using variational mode decomposition and adaptive multi-kernel based extreme learning machine technique

In this work, a six bus IEC standard model is simulated under MATLAB/SIMULINK environment with different penetration levels of islanding i.e., small, medium, and large scenarios with radial as well as in looped configuration. The three-phase current signals are extracted from each end of buses and synthesized through variational mode decomposition (VMD) to compute the spectral energy. Thereafter, subsequent features are obtained and fed into a novel adaptive multi-kernel extreme learning machine (AMKELM) classifier to classify the islanding and non-islanding cases. Different switching conditions, low impedance, and high impedance faults, and interference of noise are purposefully taken into account by looking at the real-time conditions. Finally, the performance of the proposed technique is compared with other recently published research works as well as with traditional ones to prove its efficacy over other techniques for the detection and classification of islanding scenarios.

Hilbert–Huang transform and decision tree based islanding and fault recognition in renewable energy penetrated distribution system

A fast protection algorithm based on Hilbert–Huang transform (HHT) is proposed in this paper for islanding and fault detection, classification, and location in a distribution system penetrated by a solar renewable energy source. The three-phase current signals measured at the substation are utilized to extract the instantaneous features from the first level residue using Hilbert Transform (HT) after empirical mode decomposition (EMD). The feature indices computed per phase for each event using minimum post-disturbance data are then fed to a decision tree machine learning (DTML-1) model to classify disturbances into four classes: normal, fault, islanding, and switching transient. Once a fault is determined, another DTML-2 model classifies the fault into one of the seven types of faults, namely 3P-ABC (three-phase faults), 2P-AB, 2P-BC, 2P-AC (two-phase faults), 1P-AG, 1P-BG, and 1P-CG (single-phase faults). Subsequently, seven DT models based on the fault type locate the IEEE 13 bus system’s zone of fault. Variations in noise levels, DG capacity, and fault incidence angles test the proposed algorithm to achieve a good accuracy level in less time. Switching transients like capacitor switching, feeder on/off, and transformer excitation/de-excitation are also successfully classified within a quarter cycle contaminated with noise levels of 20 dB SNR.

Improved Gaussian Filter Based Solar PV-BES Microgrid With PLL Based Islanding Detection and Seamless Transfer Control

This article presents an improved Gaussian filter with phase-locked loop based grid monitoring and seamless transfer control for solar photovoltaic-battery energy storage (PV-BES) based microgrid with improved power quality. The PV-BES microgrid comprises of a PV array and a battery, interfaced to the utility through a voltage source converter, and performs multiple tasks. In grid-connected mode, the improved Gaussian filter with quadrature signal generator-based second-order generalized integrator based prefiltering provides solar PV power to the nonlinear loads and the utility grid, along with providing reactive power compensation and power quality improvement at the point of common coupling. To regulate the power absorbed or discharged by the BES, a bidirectional converter is used. The PV feed-forward term enables PV power injection and also improves the dynamic performance of the system. On grid outage, the controller transits the PV-BES microgrid to standalone mode of operation ensuring uninterrupted supply to the load. The effectiveness of the controller is tested in various scenarios and is verified through experimentation. The controller has satisfied the specifications set by the IEEE 519-2014 power quality standard and IEEE 1547-2018 (revised) standard for interconnection and interoperability of distributed energy resources.

Zero Non-Detection Zone for Islanding Detection Based on a Novel Hybrid Passive-Active Technique with Fuzzy Inference System

Distributed generation (DG) has reformed the meaning of power generation from large scale to small scale, but unintentional islanding is the main issue when connecting DG and the utility grid. A lot of techniques have been used for detecting islanding, among these techniques, there are passive and active. The main problem of passive techniques is their large non-detection zone (NDZ), while the main drawback of active techniques is their undesirable effect on power quality. In this paper, a proposed hybrid passive–active systematic methodology based on a smart classifier that decides to use an active method instead of a passive one is presented. In the proposed scheme, sensors are used for measuring the reactive power at three terminals: the DG terminal, grid terminal, and load terminal. The novelty in this paper is the accurate detection of islanding within a shorter time either in the normal case or NDZ; also it can differentiate between islanding and grid faults without degrading the power quality of the overall system as the active technique does not have to be used continuously, and so total harmonic distortion does not exceed the standard value (5%) detected by IEEE standards. The proposed scheme was simulated using the MATLAB/Simulink platform, and the results reflect its potential with a comparative study.

Validation of Passive Islanding Detection Methods for Double Line-to-Ground Unsymmetrical Fault in a Three-Phase Microgrid System

Distributed generators (DG),double line-to-ground fault (L-L-G-Fault),non-detection zone (NDZ),point of common coupling (PCC),rate of change of frequency (ROCOF),rate of change of voltage phase angle (ROCOVPA)

Novel Passive Islanding Detection Technique by Monitoring Reverse Power at PCC

Power System of the age has included remarkable contribution of distributed energy resources (DERs). This inclusion has opened new era of research and studies. Islanding detection has become one of the important events in power system that is to be detected precisely. This study introduces a single-parameter-based passive technique for islanding detection which has zero nondetection zone without involvement of any signal processing tool. The proposed technique is tested for various islanding and nonislanding events. The simulation results prove that the suggested technique detects islanding event accurately and it is capable of distinguishing islanding and nonislanding events by an economical and simpler method.

Islanding Detection Scheme Using Potential Energy Function Based Criterion

Owning to the extensive enhancement of renewable energy resources in the distribution grids, the employment of such sources has also introduced various issues, such as the islanding problem. In this paper, an effective method is proposed for the detection of islanding in micro-grids. The proposed method employs the concept of potential energy function to drive the islanding detection index. Based on swing and potential energy function equations, an islanding detection criterion is derived based on the rate of change of the potential energy function. The islanding detection index (IDI) takes into account the frequency changes and the rate of change of frequency (ROCOF) of DG. The superiority of the proposed islanding detection method is manifested in the condition where the generation of distributed resources is in balance with the loading consumption. The performance of the proposed method has been evaluated considering the conditions where islanding is difficult to detect or might be mistaken for other phenomena given by loads within the Non-Detection Zone (NDZ) region, different fault types, and loads with different power factors. The performance evaluation has been carried out through simulations and, furthermore, has been compared with the state-of-the-art algorithms.

Unintentional Passive Islanding Detection and Prevention Method with Reduced Non-Detection Zones

Islanding detection and prevention are involved in tandem with the rise of large- and small-scale distribution grids. To detect islanded buses, either the voltage or the frequency variation has been considered in the literature. A modified passive islanding detection strategy that coordinates the V-F (voltage–frequency) index was developed to reduce the non-detection zones (NDZs), and an islanding operation is proposed in this article. Voltage and frequency were measured at each bus to check the violation limits by implementing the proposed strategy. The power mismatch was alleviated in the identified islands by installing a battery and a diesel generator, which prevented islanding events. The proposed strategy was studied on the three distinct IEEE radial bus distribution systems, namely, 33-, 69-, and 118-bus systems. The results obtained in the above-mentioned IEEE bus systems were promising when the proposed strategy was implemented. The results of the proposed strategy were compared with those of methods developed in the recent literature. As a result, the detection time and number of islanded buses are reduced.