Islanding Detection Parameters for Integrated Distributed Generation

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.

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.


2013 ◽  
Vol 318 ◽  
pp. 597-600
Author(s):  
Dong Xie ◽  
Xing Zhang

In the area of renewable energy technologies, islanding of distributed generation system needs to be prevented due to safety reasons and to ensure quality of power supplied to the customers. Several islanding detection methods based on passive and active schemes have been proposed in the literature. Passive methods have a large non detection zone (NDZ), While active schemes degrade power quality. This paper proposed a new passive islanding detection method which combines the Wavelet-transform and neural network techniques. This method can reduce the NDZ to zero without any perturbation that deteriorates the power quality. The simulation results show that the proposed islanding detection method is effective and robust in all kind of conditions.


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.


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.


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.


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.


2013 ◽  
Vol 291-294 ◽  
pp. 2057-2062
Author(s):  
Ji Hong Zhang ◽  
Pei Hong Yang ◽  
Zhen Kui Wu

The quick & exact anti-islanding is a mandatory feature for grid-connected distributed generation system. The conventional passivity detection method has the biggish blind section and lower reliability, especially when the grid-connected inverter export power and burthen power are balanceable; the islanding detection often is disabled. And that the initiative islanding detection method is considered an effective measure, but if the arithmetic & parameter choice irrelevantly, the islanding can not be detected easily; even injected harmonic to the grid and destroy power quality. An improved voltage shift technique islanding detection arithmetic is put forward in this paper, and the correlative mathematics model is established, and the project is analyzed and studied theoretically based on IEEE Std.2009-929 criterion. The result shows the method will not affect power quality, at the same time it can detect islanding phenomenon quickly& exactly, so it is feasible.


2019 ◽  
Vol 15 (2) ◽  
pp. 55-61
Author(s):  
Basanta Pancha ◽  
Rajendra Shrestha ◽  
Ajay Kumar Jha

In response to the problem of increased load demand, efforts have been made to decentralize the power utility through the use of distributed generation (DG). Despite the advantages of DG integration, un-intentional islanding remains a big challenge and has to be addressed in the integration of DG to the power system. Islanding condition occurs when the DG continues to power a part of the grid system even after the connection to the rest of the system has been lost, either intentionally or un-intentionally. The unintentional islanding mode of operation is not desirable as it poses a threat to the line workers’ safety and power quality issues. There are many methods which may be used to detect the islanding situation. Passive methods such as under/over voltage and under/over frequency work well when there is an imbalance of power between the loads and the DG present in the power island. However, these methods has larger Non Detection Zone (NDZ) and fail to detect the islanding condition if there is a balance of power supplied and consumed in the island. Remote technique of islanding detection is reliable but is not economical in small network area. Active technique of islanding detection distorts the power quality of the system as it introduces external signal in the system. This paper uses the Wavelet Transform (WT) to extract the features of voltage signal at PCC (Point of Common Coupling) and these features have been used to train Artificial Neural Network (ANN). The ANN model trained by these WT features, which understands the pattern of input feature vector, have been used to classify the islanding and non-islanding events. In this proposed method, NDZ has been efficiently eliminated which is created due to difference between active and reactive power during islanding condition. No power quality problem exists in this method as there is no disturbance injection. Hence, this proposed method is better than conventional passive and active methods.


2021 ◽  
Author(s):  
Sasan Mostafaei

This thesis presents a novel active anti-islanding detection scheme for the three phase gridconnected converters. The proposed hybrid method works based on the combination of Positive Feedback Frequency Shift (PFFS) and Reactive Power Variation (RPV) methods, and therefore it combines the features of both methods. Unlike the RPV scheme, this method is capable of synchronizing all power converters with each other in a distributed generation (DG) system. Therefore, it can effectively detect islanding when the DG system has multiple renewable energy sources interfaced to the system by multiple converters. The proposed method can also be combined with other active methods, such as the active frequency drift method. This minimizes the power quality degradation since the scheme is called upon only when 0.1Hz deviation in the grid frequency is detected. Moreover, unlike other positive feedback methods, this scheme has little impact on the stability of the DG system, since the positive feedback reference is only limited to


2021 ◽  
Author(s):  
Sasan Mostafaei

This thesis presents a novel active anti-islanding detection scheme for the three phase gridconnected converters. The proposed hybrid method works based on the combination of Positive Feedback Frequency Shift (PFFS) and Reactive Power Variation (RPV) methods, and therefore it combines the features of both methods. Unlike the RPV scheme, this method is capable of synchronizing all power converters with each other in a distributed generation (DG) system. Therefore, it can effectively detect islanding when the DG system has multiple renewable energy sources interfaced to the system by multiple converters. The proposed method can also be combined with other active methods, such as the active frequency drift method. This minimizes the power quality degradation since the scheme is called upon only when 0.1Hz deviation in the grid frequency is detected. Moreover, unlike other positive feedback methods, this scheme has little impact on the stability of the DG system, since the positive feedback reference is only limited to


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