Passive Islanding Detection Method Research Articles

Research on a new method of islanding detection based on lifting wavelet and neural network

Abstract 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.

Islanding detection of synchronous distributed generators

This paper analyses the performance of local passive islanding detection methods for synchronous distributed generators, under different grid and load scenarios. These methods monitor electrical parameters at the interconnection point of a distributed generator and detect island situation whenever these parameters change correspondingly. Lately, islanding detection research has been focused on inverter based systems. But synchronous generators still pose a challenge for study. With this aim, a low voltage distribution network with embedded synchronous generators has been modelled. The performance of frequency and rate-of-change-of-frequency relays have been evaluated, analysing the influence of power mismatch and generator characteristics on the islanding and also avoid false operation.

Passive Islanding Detection Method based on Resultant Sequence Impedance Component and Load Shedding in Islanded Area

Passive Islanding Detection Method based on Resultant Sequence Impedance Component and Load Shedding in Islanded Area

A hybrid IDM using wavelet transform for a synchronous generator-based RES with zero non-detection zone

<abstract> <p>Increased use of renewable energy sources in distribution grids has led to the growing concern over unintentional islanding. Among the available islanding detection methods, the passive methods have larger non-detection zones and are susceptible to system faults. However, they have no effect on power quality like active methods. We present a hybrid method for the islanding detection of synchronous generator-based renewable energy sources. Here, the larger non-detection zone issue of the passive islanding detection method was reduced by combining it with a wavelet transform. The rate of change of a voltage unbalanced factor was computed from the sequence components of the renewable energy source terminal voltage. Then, the factor was analyzed using a wavelet transform, and a threshold for the factor was found. The robustness of the method was tested for several islanding as well as non-islanding situations. The efficacy of the method was also tested in multi-source test systems. From the analysis, it was observed that the proposed method was fast, reliable, and had a zero non-detection zone.</p> </abstract>

A Novel Passive Islanding Detection Method for Distributed Generation

Off-grid and On-grid are two technologies that allow renewable energy sources to run continuously. The system can be networked in the first scenario, and it can operate independently or as a microgrid in the second. The decentralised generator (DG) can run in island mode even if there isn't an external power supply accessible. This circumstance may prohibit the equipment from correctly joining, endangering the auxiliary system. In order to find island patterns at particular times, this research suggests a passive method. There may be problems with island detection (ID) when using DG systems like P.V. Additionally, the identification accuracy will be impacted by the quantity of DG devices in the power distribution system. The suggested remedy has really been put into practice in a test example involving a network-connected DC power source operating at 415 V and 50 Hz. The MATLAB Simulink environment was used to assess the method's efficacy. This technique speeds up detection and improves the THD.

A Novel Islanding Detection Method for Distributed PV System Based on μPMUs

With the rapid development of distributed PV systems in distribution grids, unintentional islanding is one major concern which maybe cause safety hazards. The existing passive islanding detection methods are mainly based on the voltage and frequency deviations during islanding conditions. Passive methods have relatively large non-detection zone (NDZ) and susceptible to power system faults. Active islanding detection methods applied in inverters have relatively small non-detection zone, but they are usually harmful to power quality. This paper presents a new islanding detection method based on equivalent inter-connection line impedance, which is normally a small value. A measured impedance is calculated with the synchronous phasors from two lPMUs which are installed in a utility substation and a PV system. Under the grid-connected condition, the measured impedance is no more than the equivalent line impedance. While under the islanding condition, the measured impedance is much larger than the equivalent line impedance. So, an islanding condition can be effectively detected by the comparison of the measured impedance with the equivalent line impedance. The non-detection zone of this proposed method is nearly zero. The detection time is normally less than 250ms. This method is applicable for PV systems connected to the power system with a distribution transformer. It is also applicable for a distribution grid with multiple distributed generation systems.

Islanding Issues, Consequences, and a Robust Detection Method for Hybrid Distributed Generation Based Power Systems

Islanding refers to the situation where a Distributed Energy Resource (DER) remains as the sole power supply for a specific section of a power system, even after the main utility grid has been cut off. Suitable islanding detection is crucial to maintain the stability and dependability of a power distribution system that includes DERs. Islanding detection using easy-to-implement passive techniques exhibits a cost-effective response. The purpose of this study was to examine the causes and effects of islanding that a system can experience and propose a passive islanding detection method that uses ROCOPAD. The effectiveness of the proposed method was assessed using a MATLAB Simulink-based power system integrated with multiple Distributed Generations (DGs). The results showed that the proposed ROCOPAD-based islanding detection provided the best results. Evaluation metrics, including detection accuracy, false operation, and detection time, highlighted the effectiveness of the proposed approach.

Intelligent Island detection method of DC microgrid based on Adaboost algorithm

Aiming at the problems of large detection blind areas and difficult threshold settings in traditional passive islanding detection methods, this paper proposes an intelligent passive islanding detection method based on the adaptive boosting (Adaboost) algorithm. This method first uses feature screening technology to obtain the key feature electrical quantities of DC microgrid islands and form a sample set, and then rely on the Adaboost algorithm to generate a high-precision island classification model to realize the detection and classification of DC microgrid operation status. It has the advantages of automatic setting threshold, small detection blind area, and high accuracy. In addition, aiming at the problem that the classification results of the intelligent islanding detection algorithm based on machine learning cannot be directly used as the islanding discrimination results, an islanding criterion method based on the sliding window algorithm is added on the basis of the classification algorithm. This method realizes the accurate detection of the DC microgrid islanding operation state by the secondary analysis and judgment of the classification results of the islanding classification model. Finally, a DC microgrid model is built to simulate and verify the proposed method. The results show that the method can quickly and accurately complete the islanding detection of the DC microgrid.

A Novel Passive Islanding Detection Method for a Microgrid Using Instantaneous Energy

A Novel Passive Islanding Detection Method for a Microgrid Using Instantaneous Energy

A novel CSoDoA based passive islanding detection technique for multi‐DER AC microgrid control

AbstractMicro‐grid islanding methods are gaining importance as the presence of renewable energy resources is becoming increasingly popular in power distribution. Among all the islanding methods, passive methods are easy to implement and applicable to all types of DERs provided the NDZ is minimized. This article presents a novel passive islanding detection method based on the CSoDoA of ellipse formed by the successive phase voltages to address the NDZ problem. The peak magnitude and phase angle difference of voltages are the parameters to be estimated to compute the area of the ellipse. State‐of‐the‐art passive methods consider the effect of either magnitude or phase angle or frequency as an islanding detection metric. The CSoDoA metric combines the effect of both magnitude and phase angle thereby reducing the NDZ. The proposed method is validated on both synchronous and inverter‐interfaced DERs. The test systems considered are both single‐DER based MG and modified IEEE 13 bus multi‐DER MG. The CSoDoA algorithm is implemented on a Raspberry‐Pi controller and validated using HIL workbench with real‐time simulator OP‐4510. Various islanding and non‐islanding events are simulated, tested and it is evident from the results that it has a very small NDZ.

A Novel Approach for Secure Hybrid Islanding Detection Considering the Dynamic Behavior of Power and Load in Electrical Distribution Networks

In the arena of modern electrical power distribution systems, distributed generators (DGs) are emerging as a manifestation of electric power personalization. Even though DGs have various advantages, unintentional islanding phenomena caused by DGs during abnormal grid operations can damage equipment connected to the grid. Therefore, islanding detection mechanisms are essential for DGs in grid-connected mode to disconnect the DG from the grid in case of grid abnormalities by obeying to specific grid codes. In this regard, a novel approach to develop a secure hybrid islanding detection method (IDM) is presented in this paper. The proposed hybrid IDM is developed by combining two passive IDMs known as rate of change of active power and rate of change of reactive power with an active IDM called load connecting strategy. An 11 kV Malaysian distribution system integrated with three types of DGs, namely synchronous generator, photovoltaic, and biomass, has been chosen as a testbed for the verification of the proposed hybrid IDM. Seven different case studies have been conducted in the PSCAD/EMTDC platform to validate the performance of the proposed IDM for islanding and non-islanding events. The simulation results confirm that the proposed IDM can detect islanding within 0.09 s, which is within 2 s complying with IEEE and IEC standards. Further, a comparative study based on the detection time and non-detection zone has been carried out, which has confirmed that the proposed IDM demonstrates better performance compared to the previously developed hybrid IDMs.

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.

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.

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.

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)

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.

A Survey of Islanding Detection Methods for Microgrids and Assessment of Non-Detection Zones in Comparison with Grid Codes

Detection of unintentional islanding is critical in microgrids in order to guarantee personal safety and avoid equipment damage. Most islanding detection techniques are based on monitoring and detecting abnormalities in magnitudes such as frequency, voltage, current and power. However, in normal operation, the utility grid has fluctuations in voltage and frequency, and grid codes establish that local generators must remain connected if deviations from the nominal values do not exceed the defined thresholds and ramps. This means that islanding detection methods could not detect islanding if there are fluctuations that do not exceed the grid code requirements, known as the non-detection zone (NDZ). A survey on the benefits of islanding detection techniques is provided, showing the advantages and disadvantages of each one. NDZs size of the most common passive islanding detection methods are calculated and obtained by simulation and compared with the limits obtained by ENTSO-E and islanding standards in the function of grid codes requirements in order to compare the effectiveness of different techniques and the suitability of each one.

Multivariable passive method for detection of islanding events in renewable energy based power grids

Penetration of distributed generation resources (DGR) in power grid is rapidly increasing to meet future energy demand efficiently. It helps in mitigating the problems of high carbon emission, green house effect, and increased cost of oil and natural gases. Island formation of a part of the renewable energy based power grid (REPG) creates hazards to operating personnel and equipments. Hence, efficient identification of islanding condition and disconnection of DGR immediately become essential for avoiding damage to equipment, personnel safety hazards and grid protection. This paper investigated a signal processing based passive islanding detection method (IDM) which is effective with the availability of multi-DGR. A islanding detection factor (MIDF) using multi-variables is proposed which is computed using features extracted by processing the voltage signal, negative sequence current (NSC) and negative sequence voltage (NSV) using Stockwell transform (ST) and Hilbert transform (HT). Total harmonic distortions of voltage ( T H D v $THD_{v}$ ) and current ( T H D i $THD_{i}$ ) are also considered to compute MIDF. Islanding event is recognized and differentiated from non-islanding conditions by comparing the MIDF with two threshold values. This method effectively detects the islanding event and discriminates it from the operational and faulty events. IDM has small non-detection zone (NDZ) and low computational time. Performance of IDM is not affected by noisy environment. Effectiveness of the IDM is established by testing for different event incidence angles, various fault impedances, different values of loads and capacitors, and different penetration levels of RE. Efficacy of IDM is established by testing the IDM through an elaborated study on IEEE-13 bus distribution grid interfaced with wind power plant (WPP) and solar power plant (SPP). Further, IDM is effectively implemented to detect the islanding event created on a practical distribution network. Effectiveness of IDM is better in comparison to IDMs designed by applications of discrete wavelet transform (DWT), empirical mode decomposition (EMD), Slantlet Transform and Ridgelet probabilistic neural network (RPNN), artificial neural network (ANN), change in rate of active and reactive power, rate of change of frequency, and rate of change of voltage angle.

Hybrid islanding detection technique for distribution network considering the dynamic behavior of power and load

AbstractNowadays, 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.

A Decentralized Passive Islanding Detection Method Based on the Variations of Estimated Droop Characteristics

A microgrid including distributed generators can operate connected to the main electrical network or in an isolated manner, referred to as island operation. The transition between both states can occur voluntarily, but a disconnection can also happen unexpectedly. The associated transients can be harmful to the grid, and compensating actions must be triggered to avoid service interruption, preserve power quality, and minimize the possibility of faults; island detection methods are essential to this end. Such techniques typically depend on communication networks or on the introduction of minor electrical disturbances to identify and broadcast unexpected islanding events. However, local energy resources are distributed, variable, and are expected to be integrated in a plug-and-play manner; then, conventional island detection strategies can be ineffective as they rely on specific infrastructure. To overcome those problems, this work proposes a straightforward, distributed island detection technique only relying on local electrical measurements, available at the output of each generating unit. The proposed method is based on the estimated power-frequency ratio, associated with the stiffness of the grid. A “stiffness change” effectively reveals island operating conditions, discards heavy load variations, and enables independent (distributed) operation. The proposal was validated through digital simulations and an experimental test-bed. Results showed that the proposed technique can effectively detect island operation at each generating unit interacting in the microgrid. Moreover, it was about three times faster than other reported techniques.