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

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 460
Author(s):  
José Antonio Cebollero ◽  
David Cañete ◽  
Susana Martín-Arroyo ◽  
Miguel García-Gracia ◽  
Helder Leite

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.

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3479 ◽  
Author(s):  
Mehdi Hosseinzadeh ◽  
Farzad Rajaei Salmasi

This paper provides an overview of islanding fault detection in microgrids. Islanding fault is a condition in which the microgrid gets disconnected from the microgrid unintentionally due to any fault in the utility grid. This paper surveys the extensive literature concerning the development of islanding fault detection techniques which can be classified into remote and local techniques, where the local techniques can be further classified as passive, active, and hybrid. Various detection methods in each class are studied, and advantages and disadvantages of each method are discussed. A comprehensive list of references is used to conduct this survey, and opportunities and directions for future research are highlighted.


Author(s):  
S. Govinda Raju ◽  
K. Harinadha Reddy ◽  
Ch. Rami Reddy

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.


Mathematics ◽  
2021 ◽  
Vol 9 (24) ◽  
pp. 3174
Author(s):  
Muhammed Y. Worku ◽  
Mohamed A. Hassan ◽  
Luqman S. Maraaba ◽  
Mohammad A. Abido

Microgrids that are integrated with distributed energy resources (DERs) provide many benefits, including high power quality, energy efficiency and low carbon emissions, to the power grid. Microgrids are operated either in grid-connected or island modes running on different strategies. However, one of the major technical issues in a microgrid is unintentional islanding, where failure to trip the microgrid may lead to serious consequences in terms of protection, security, voltage and frequency stability, and safety. Therefore, fast and efficient islanding detection is necessary for reliable microgrid operations. This paper provides an overview of microgrid islanding detection methods, which are classified as local and remote. Various detection methods in each class are studied, and the advantages and disadvantages of each method are discussed based on performance evaluation indices such as non-detection zone (NDZ), detection time, error detection ratio, power quality and effectiveness in multiple inverter cases. Recent modifications on islanding methods using signal processing techniques and intelligent classifiers are also discussed. Modified passive methods with signal processing and intelligent classifiers are addressing the drawbacks of passive methods and are getting more attention in the recently published works. This comprehensive review of islanding methods will provide power utilities and researchers a reference and guideline to select the best islanding detection method based on their effectiveness and economic feasibility.


2013 ◽  
Vol 845 ◽  
pp. 283-286 ◽  
Author(s):  
Malik Abdul Razzaq Al Saedi ◽  
Mohd Muhridza Yaacob

There is a high risk of insulation system dielectric instability when partial discharge (PD) occurs. Therefore, measurement and monitoring of PD is an important preventive tool to safeguard high-voltage equipment from wanton damage. PD can be detected using optical method to increase the detection threshold and to improve the performance of on-line measurement of PD in noise environment. The PD emitted energy as acoustic emission. We can use this emitted energy to detect PD signal. The best method to detect PD in power transformer is by using acoustic emission. Optical sensor has some advantages such as; high sensitivity, more accuracy small size. Furthermore, in on-site measurements and laboratory experiments, it isoptical methodthat gives very moderate signal attenuations. This paper reviews the available PD detection methods (involving high voltage equipment) such as; acoustic detection and optical detection. The advantages and disadvantages of each method have been explored and compared. The review suggests that optical detection techniques provide many advantages from the consideration of accuracy and suitability for the applications when compared to other techniques.


2014 ◽  
Vol 699 ◽  
pp. 546-551 ◽  
Author(s):  
Ahmad Farid Sapar ◽  
Chin Kim Gan ◽  
Meysam Shamshiri ◽  
Anis Niza Ramani

The awareness concerning the grid connected Photovoltaic (PV) has become vital and a major concern nowadays. Islanding detection is one of the most dominant challenges for distributed generation system connected to the utility grid. In addition, islanding has not been a preferable option as it may pose safety hazard and may cause damage to power generation and power supply facilities as a result of unsynchronized re-closer. Therefore, the islanding detection techniques are needed to ensure safe and reliable system operation. One of the established islanding prevention methods is the Slip Mode Frequency Shift (SMS) islanding method, which has numerous advantages over the other techniques. This paper investigates the active islanding detection methods and specifically focused on the SMS islanding method. The results show that the SMS islanding method successfully detected an unintentional fault and managed to isolate the system within the prescribed time range.


2011 ◽  
Vol 23 (No. 3) ◽  
pp. 85-92 ◽  
Author(s):  
P. Dostálek ◽  
T. Brányik

This review surveys rapid bioluminescent detection techniques applied in food industry and discusses the historical development of the rapid methods. These techniques are divided into two groups: methods based on bioluminescent adenosine triphosphate (ATP) assay, and on bacterial bioluminescence. The advantages and disadvantages of these methods are described. The article provides the bibliography of fluorescent method applications in food samples.    


Author(s):  
MARCOS VINICIOS GOMES DOS REIS ◽  
MARCELO GRADELLA VILLALVA ◽  
DANTE INGA NARVAEZ ◽  
LUCAS SAVOI DE ARAÚJO ◽  
HUGO SOEIRO MOREIRA ◽  
...  

Aerospace ◽  
2019 ◽  
Vol 6 (11) ◽  
pp. 117 ◽  
Author(s):  
Luis Basora ◽  
Xavier Olive ◽  
Thomas Dubot

Anomaly detection is an active area of research with numerous methods and applications. This survey reviews the state-of-the-art of data-driven anomaly detection techniques and their application to the aviation domain. After a brief introduction to the main traditional data-driven methods for anomaly detection, we review the recent advances in the area of neural networks, deep learning and temporal-logic based learning. In particular, we cover unsupervised techniques applicable to time series data because of their relevance to the aviation domain, where the lack of labeled data is the most usual case, and the nature of flight trajectories and sensor data is sequential, or temporal. The advantages and disadvantages of each method are presented in terms of computational efficiency and detection efficacy. The second part of the survey explores the application of anomaly detection techniques to aviation and their contributions to the improvement of the safety and performance of flight operations and aviation systems. As far as we know, some of the presented methods have not yet found an application in the aviation domain. We review applications ranging from the identification of significant operational events in air traffic operations to the prediction of potential aviation system failures for predictive maintenance.


Author(s):  
Abbineni Sai Subhadra ◽  
P.Linga Reddy ◽  
Shailesh . B Modi

Islanding detection of Distributed Generation (DG) is considered as one of the most important aspects when interconnecting DGs to the distribution system. It was the crucial problem in distributed generation. This detection phenomenon having a great importance. These detection methods are divided into active and passive islanding detection. These two methods are based on changing in parameters such as frequency, voltage and current harmonics. But these methods have some challenges such as reduction in power quality and large Non Detection Zone (NDZ). In this paper, the proposed method is change of Total harmonic distortion (THD) will be studied for islanding detection diagnosis. The studied system was considered by following the standard IEEE-1547 and UL-1741.The system was simulated using MATLAB/ SIMULINK.


2019 ◽  
Vol 2 (3) ◽  
pp. 25 ◽  
Author(s):  
Ashish Shrestha ◽  
Roshan Kattel ◽  
Manish Dachhepatic ◽  
Bijen Mali ◽  
Rajiv Thapa ◽  
...  

The issue of unintentional islanding in grid interconnection still remains a challenge in grid-connected, Distributed Generation System (DGS). This study discusses the general overview of popular islanding detection methods. Because of the various Distributed Generation (DG) types, their sizes connected to the distribution networks, and, due to the concern associated with out-of-phase reclosing, anti-islanding continues to be an issue, where no clear solution exists. The passive islanding detection technique is the simplest method to detect the islanding condition which compares the existing parameters of the system having some threshold values. This study first presents an auto-ground approach, which is based on the application of three-phase, short-circuit to the islanded distribution system just to reclose and re-energize the system. After that, the data mining-decision tree algorithm is implemented on a typical distribution system with multiple DGs. The results from both of the techniques have been accomplished and verified by determining the Non-Detection Zone (NDZ), which satisfies the IEEE standards of 2 s execution time. From the analysis, it is concluded that the decision tree approach is effective and highly accurate to detect the islanding state in DGs. These simulations in detail compare the old and new methods, clearly highlighting the progress in the field of islanding detection.


Sign in / Sign up

Export Citation Format

Share Document