Islanding Detection Scheme Research Articles

Superimposed Positive Sequence Impedance for Detecting Unintentional Islanding in Microgrid

Incorporation of environmentally friendly energy sources (RESs) into the electricity grid has many benefits, including economic, technological, and environmental. However, excessive renewable energy sources (RES) in the power grid provide technical problems, including equipment protection, DG operation, and islanding detection. One of the most serious challenges is the islanding phenomenon. Islanding can cause several problems, such as frequency instability and voltage fluctuations resulting in damage to electrical equipment or threatening utility workers who may be working/accessing the equipment. This research proposes an efficient islanding detection algorithm to lessen the impact of such threats. This novel passive islanding detection scheme is based on superimposed positive sequence impedance (SPSI). For calculating the superimposed positive sequence impedance (SPSI), the voltage and current signals are obtained from targeted DG points. The scheme’s performance is tested on multiple bus systems across islanding and non-islanding conditions using a MATLAB/Simulink environment. It is shown that even in the presence of noise, the algorithm can determine an islanding decision with high accuracy and a short detection time of 84 ms. In comparison to other algorithms, it operates at zero power mismatch (ZPM) and does not affect power quality.

Design and verification of q-axis perturbation based active islanding detection schemes for DG systems

The penetration of grid integrated distributed generation (DG) in the present decade, has benefited rural communities, the environment, and the power sector. These renewable power sources based DGs could eliminate the need of extensive transmission networks, especially in remote areas, reduce emissions and improve power supply reliability. A significant drawback of grid integrated DG systems is the islanding of DG units, which puts workers' safety at risk and raises the possibility of damaging electrical infrastructure. Therefore, islanding detection techniques are used to reduce the danger associated with islanded functioning of DG units. Fast detection, small non detection area and less power quality disturbance are the major requirements of any islanding detection method. To address this issue of islanding, researchers have proposed various islanding detection strategies. This paper compares various q-axis controller-based islanding identification approaches: sub-harmonic perturbation (SHP), complementary reactive power perturbation (CRPP), and even harmonic perturbation (EHP). In all three proposed methodologies, the perturbations introduced result in frequency deviations surpassing the predefined threshold values. But the time of islanding detection is least in the CRPP approach. CRPP can also drift the total harmonic distortion (THD) beyond the corresponding threshold in an appreciable way. The performance of these (Islanding detection methods) IDMs is evaluated through simulations using MATLAB-Simulink on a PV fed DG. The efficacy of the comparative analysis is ensured with necessary waveforms.

Triple‐indexed passive islanding detection strategy for grid‐connected distributed generation networks using an extended Kalman filter

AbstractIslanding detection is a challenging issue in modern grid‐connected distributed generation networks (GCDGN). Generally, islanding detection has two categories local and remote, local schemes can be categorized into active, passive, and hybrid schemes. This article proposes a triple‐indexed passive islanding detection (TIPID) scheme using an extended Kalman filter (EKF). Initially, the EKF algorithm is applied on voltage signal at the point of the common coupling to estimate the desired fundamental and non‐fundamental features. The first index, known as the cumulative voltage logarithmic index, is computed by taking the natural logarithm of the fundamental voltage features to detect any variations in the GCDGN. The second index, known as the voltage differentiation index (VDI), is calculated from the fundamental voltage features, while the third index, known as the odd‐order harmonic distortion index (OOHDI), is obtained from the non‐fundamental odd‐order harmonics of the PCC voltage. Then, the VDI and OOHDI are compared to pre‐defined threshold to detect/distinguish islanding events. The proposed TIPID method is validated through extensive simulations on the IEEE 13‐bus test bed via MATLAB/Simulink 2022b. Results show that under both balanced/unbalanced load & generation, the proposed TIPID approach detects islanding occurrences with reduced non‐detection zone (NDZ) in less than 5 ms.

Islanding Detection and Power Quality Diagnosis of Wind Power Integrated Microgrid with Reduced Feature Trained Novel Optimized Random Decision Forest

Distributed generations (DGs) have been increasingly addressing the ongoing power deficit in the electricity market. However, a significant concern in DG-integrated microgrids is the detection of accidental islanding. To tackle this issue, this article proposes a cost-friendly, novel data-driven passive islanding detection scheme named EEMD-HOBRC, combining noise-assisted ensemble empirical mode decomposition (EEMD) and a hybrid optimization-based random forest classifier (HOBRFC). The detection scheme employs a diverse set of features extracted from both raw and EEMD decomposed signals. Essential features are selected using the binary grey wolf optimizer (BGWO) to reduce computational burden. To further improve classification accuracy, the parameters of the random forest classifier are optimized through a hybrid particle swarm and reformed grey wolf optimization (PSRGWO) technique with Cohen’s kappa index as the cost function. The proposed technique is rigorously validated in two different multi-DG environments, encompassing islanding and various nonislanding events. The results demonstrate the effectiveness of the approach in terms of enhanced accuracy, detection time, and performance under both noisy and noise-free conditions. The accuracy of detection under ideal and high noise scenarios is found to be 99.88% and 99.2%, respectively, with maximum detection time of 34.27 ms. Comparative analysis with other algorithms also supports the superiority of the proposed technique. Finally, the method is successfully applied to shrink the nondetection zone (NDZ) with minimal power mismatch, further enhancing its utility in practical applications.

Performance of Power-Line-Signaling Based Detection Algorithms for Islanding Protection of Distributed Generators in Interharmonic Polluted Systems

Recently, a new islanding detection scheme based on power electronic signaling technology has been proposed in the literature. By broadcasting a signal on the distribution feeders from the substation to the down-stream DGs, the absence of the signal at the DG site will be a sign of islanding. The scheme is more reliable than regular local detection techniques while it costs much less than transfer trip schemes. As the checking of the signal continuity is done via signal detectors, performance analysis of implemented detection algorithms is one of the main concerns. Since, the scheme relies on distortion broadcasting, our purpose is to answer the first question arises i.e., `` Is it a reliable scheme for DGs located at industrial areas that are rich in harmonics and interharmonics? ". Results show that for spectral based detection algorithms, more selective thresholds must be set in case of excessive interharmonic pollutions.

Real-time analysis of islanding detection scheme developed for AC microgrid system

Real-time analysis of islanding detection scheme developed for AC microgrid system

Particle Filter-based Passive Islanding Detection Scheme for Renewable Energy Penetrated Distribution Systems

Particle Filter-based Passive Islanding Detection Scheme for Renewable Energy Penetrated Distribution Systems

Passive Islanding Detection Scheme Based on Instantaneous Voltage and Current for a Multi-DG Microgrid

Passive Islanding Detection Scheme Based on Instantaneous Voltage and Current for a Multi-DG Microgrid

A communication-less islanding detection scheme for hybrid distributed generation systems using recurrent neural network

The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems that include both synchronous and inverter-based DG devices. The scheme consists of three stages: time-domain feature extraction (FE) from the three-phase voltage signal at the point of common coupling (PCC), feature selection using the wrapper method, and detection using a long short-term memory (LSTM) RNN algorithm. To assess the performance of the proposed scheme, a comprehensive set of islanding and grid-connected scenarios was created using the IEC 61850-7-420 test system in MATLAB/Simulink. After feature extraction in MATLAB, the feature selection and LSTM model training/testing steps were conducted in Python. Thirteen features were extracted from the voltage signal, and the most significant features were selected for detection using the wrapper method. The detection process encompassed various events, such as line faults, load switching, and capacitor switching, occurring in both islanded and grid-connected modes. The proposed scheme was compared against existing techniques, artificial neural networks, and support vector machines under the same conditions. The proposed scheme demonstrated excellent accuracy (99.68 %), selectivity (99.44 %), and sensitivity (100 %) under normal conditions with all features. It also performed well in noisy environments, with accuracies of 98.94 % and 97.04 % with 40 dB and 30 dB noise, respectively. This research highlights the importance of quality and quantity of data for training intelligent RNN-based IDSs and demonstrates the effectiveness of the proposed scheme in detecting islanding in hybrid DG systems.

New Passive Loss of Mains Detection Scheme Using Characteristics of Differential Impedance of Series Inductor

Nowadays, renewable energy sources (RESs) are widely used as distributed generation sources, leading to issues such as unintentional islanding, protection concerns, and reverse power flow. Unintentional islanding is dangerous because it can endanger utility workers, damage DG units, and jeopardize grid stability. To overcome these issues, Researchers are developing islanding detection schemes. This article proposes a novel passive technique for islanding detection of multi-bust test systems, based on the differential impedance of a series inductor. The differential impedance changes during islanding and non-islanding events. However, in grid-connected mode, the voltage and frequency of the microgrid are handled by the utility grid. Therefore, no significant changes in differential impedance occur. The voltage and frequency of the microgrid are not handled by the power grid while in islanded mode. Therefore, the differential impedance varies significantly. The islanding is detected if the value of differential impedance is greater than the predefined threshold. This scheme detects islanding in 24 ms at zero mismatch power, has no impact on power quality, and is computationally simple. The proposed approach easily discriminates between islanding and non-islanding events. The distribution test system is simulated in MATLAB/Simulink environment. Additionally, the novel passive technique has been validated on an OPAL-RT real-time platform.

RFMFA Technique for Islanding Detection Scheme in Integrated DG System

EEE 1547 specifies time limits for the completion of DG interconnection tasks, and one of these tasks is the detection of islanding, which must be completed within two seconds of the task's start. This thesis provides new and effective islanding detection algorithms for a hybrid distributed generating system connected to the grid. The suggested technique is a hybrid of two different optimization algorithms: Random Forest (RF) and Moth Flame Optimization (MFO). At the objective stage, this technique employs the ROCOF. The suggested methods are distinguished by their ease of use due to the lack of a mandatory minimum. Furthermore, they are unaffected by the capacity or kind of Distributed Generation linked to the utility grid and not affected by system factors. In addition, the NDZ is not present after applying these processes. When compared to the standard approaches, these methods show a marked improvement in their ability to classify events into islanding and non-islanding categories. Several elements, including varying load situations, switching operations, and network conditions, must be considered before determining the proposed solutions' viability. The MATLAB/Simulink platform provides a setting where the suggested procedures may be implemented.

A New Variational Mode Decomposition-Based Passive Islanding Detection Strategy for Hybrid Distributed Renewable Generations

A New Variational Mode Decomposition-Based Passive Islanding Detection Strategy for Hybrid Distributed Renewable Generations

Preserving microgrid sustainability through robust islanding detection scheme ensuring cyber-situational awareness

Along with the numerous environmental and operational benefits of renewable energy sources (RESs) integration into modern distribution networks, maintaining system security in these networks during challenging phenomena, especially unintentional islanding can still be problematic in some cases. This paper puts forward a sensitivity-based islanding detection algorithm that utilizes the transient kinetic energy of the RESs to identify the islanding condition in microgrids and also considers cyber-attacks, which may lead to operators making inappropriate operational choices. To be specific, the proposed algorithm finds a generalized index that considers simultaneously the impact of volatility of parameters during islanding and non-islanding conditions and is also robust against data integrity attacks. The generalized index, the so-called sensitivity islanding detection (SID) index, is designed based on the sensitivity of transient kinetic energy over transient influential parameters. Furthermore, a statistical index for islanding detection is introduced based on the standard variation that effectively monitors the volatilities. An unsupervised anomaly detection method that uses kernel density estimation technology and statistical calculations are proposed as a way to find cyber-attacks. Following that, an outlier detection method is used to identify anomalies. The effectiveness of the proposed algorithm is evaluated under various conditions using simulation environments.

1D recursive median filter based passive islanding detection strategy for grid‐connected distributed generations network

AbstractIn modern distribution networks, integration of distributed generations (DGs) at consumer premises is common. However, islanding detection in such a grid‐tied distributed generation (GTDG) network is the topmost challenge to ensure power quality and reliable operation. This paper presents a modified passive islanding detection scheme (MPIDS) for the GTDG network, using a One‐D recursive Median filter (ODRMF) algorithm. Firstly, at the point of common coupling (PCC), 3‐phase voltage is acquired. Next, the ODRMF is employed to extract 3rd harmonic and residuals from the acquired voltage signal. Afterward, two novel islanding detection indices developed are: (1) First change detection (FCD), which is calculated from the residuals, and (2) delta selected harmonic distortion (∆SHD), which is computed from 3rd harmonic content of the voltage signal. Finally, variations in the two indices are compared with the threshold to identify islanding. To validate the efficacy of the presented MPIDS, rigorous simulations in MATLAB/ Simulink are conducted on the UL‐1741 and IEEE 13‐bus GTDGs systems under different conditions. The results illustrate that the presented strategy is highly reliable in all assessed conditions and can detect the islanding as well as non‐islanding incidents effectively under balanced and unbalanced load/generation conditions with a very low non‐detection zone.

A Digital Lock-In Amplifier Assisted Active Islanding Detection Technique for DC Microgrids

Islanding detection is crucial in both AC and DC grids, failure of which might result in unstable operating points. This is a key impediment to increase renewable energy integration. Islanding detection in the DC grid is relatively a new concept as compared to AC grid islanding. In the DC grid, islanding detection majorly depends upon threshold settings with respect to under/over voltage limits (which fail during zero power mismatch (ZPM) conditions). Some active islanding techniques focus on disturbance injection, but the larger disturbance in those techniques causes unstable operations in the grid. This research proposes an impedance-based active islanding detection scheme to address the shortcomings of existing techniques. The digital Lock-In Amplifier (D-LIA) and sensors in PV are used to accomplish the approach. The proposed scheme can detect islanding during the ZPM scenario without any degradation of power quality. This scheme can discriminate islanding conditions efficiently with a disturbance injection of lower magnitude. The proposed active islanding detection technique is modeled in MATLAB/Simulink, with experimental validation on a DC Microgrids hardware test bed with the dSPACE (DSP-1104) controller.

Status and Prospect of Islanding Detection in Active Distribution Network

A large number of distributed power sources are injected to the distribution network, which can cause island operation in planned or unplanned situations. The islanded operation caused by the fault will cause the inverter to go off the grid in serious fault conditions such as short circuit between phases and disconnection. After the island is formed, if the common connection point before the island exchanges more power, a sudden change in the voltage within the island occurs. The frequency and phase angle changes of the voltage in the island are closely related to the characteristics of the inverter phase-locked loop, and the frequency mutation generally does not cause sudden changes in frequency due to a certain inertia of the phase-locked loop. Due to sudden changes in load power angle, input fault ride-through, etc., sudden changes in the phase angle of voltage in islands may occur. In order to solve the possible problems of power quality deterioration in islands, passive, active, and remote islanding detection schemes can be adopted, and the three schemes have their own advantages and disadvantages. In actual operation, it is necessary to consider the cooperation relationship between island detection, protection, safe automatic control and fault ride through.

A Fault and Islanding Detection Scheme using Differential Positive Sequence Power Angle for a Microgrid

Implementation of distributed generation (DG) fault and islanding detection in a microgrid are two difficult jobs to complete. Efforts by many researchers to develop solutions to these a kind of challenges are ongoing. Still, there is hardly any scheme that can detect and distinguish both the fault and islanding events. To detect and differentiate between fault and islanding events, this article presents a Differential Positive Sequence Power Angle (DPSPA)-based protection technique. The scheme is widely examined considering different working conditions of a microgrid such as DG disconnection, DG penetration, different fault parameters like fault type, fault resistance, fault location, fault inception angle, fault during single-pole tripping (STP), simultaneous faults, and evolving faults. Tests were also performed for non-fault cases like load switching, capacitor switching, sectional cut-off, DG disconnection, and impact of noise and sampling frequency. Furthermore, the scheme’s outcomes have been compared to that of recent protection schemes. Finally, using the OP4510 real-time simulator, the proposed approach is validated in an online environment. The results show that the proposed DPSPA-based scheme can be a notable scheme to protect a microgrid in a wide variety of situations.

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.

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.

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.