scholarly journals Improved ROCOF relay for islanding detection of solar distributed generation

2019 ◽  
Vol 14 (3) ◽  
pp. 1105 ◽  
Author(s):  
J. Rajesh Reddy ◽  
A. Pandian
Keyword(s):  
Distributed Generation ◽  
Fossil Fuels ◽  
Reactive Power ◽  
Rate Of Change ◽  
Islanding Detection ◽  
Detection Zone ◽  
Detection Scheme ◽  
Renewable Distributed Generation ◽  
Power Injection ◽  
Effective Performance

<p>In recent years to meet the energy consumption demand of the world, all are working on renewable distributed generation (RDG) due to shortage of fossil fuels. The RDG systems after integrating with grid, has a disadvantage of islanding in the power system. Islanding is caused, if the RDG is supplying power to load connected due to failures in the grid. As per IEEE 1547 distributed generation (DG) interconnection standards, the islanding should be detected within 2 seconds after islanding. In this paper a hybrid islanding detection scheme is presented with rate of change of frequency (ROCOF) and reactive power injection with positive feedback. It will reduce the non detection zone (NDZ) of passive ROCOF relay to zero and can detect balanced islanding. The computer simulations are performed on MATLAB-2016. The simulations results show the effective performance of the proposed method.</p>

scholarly journals Islanding Detection Scheme of Distributed Generation Systems using Hybrid FAT-SGO Approach

2020 ◽  
Vol 10 (1) ◽  
pp. 213-218
Keyword(s):  
Comparative Analysis ◽  
Standard Deviation ◽  
Distributed Generation ◽  
Rate Of Change ◽  
Statistic Analysis ◽  
Islanding Detection ◽  
Detection Zone ◽  
Detection Thresholds ◽  
Switching Operation ◽  
Detection Scheme

In this paper an effective hybrid FAT-SGO approach is proposed for islanding detection of distributed generation (DG) system. The proposed approach is the joint implementation of Feedback Artificial Tree (FAT) and Shell Game Optimization (SGO) named as FAT-SGO technique. Reducing the non-detection zone (NDZ) as near as possible and keep the output power quality unmovable is main contribution of this paper. Furthermore, this method solves the issue of establishing detection thresholds inherent in existing methods. The proposed strategy uses the rate of change of frequency (ROCOF) in DG destination location is utilized as input sets of FAT system for intelligent islanding detection. Here, FAT is trained by SGO, which extracts the different intrinsic characteristics among islanding and grid disturbance. With the extracted characteristics, the FAT method is used for classifying the disturbances in islanding and grid. For authenticating the feasibility of this strategy is authorized through various conditions and different conditions of load, switching operation, and network. The simulation of the proposal is done in MATLAB / SIMULINK and the performance in islanding and non-islanding events was studied. Statistic analysis of proposed and existing methods of mean, median and standard deviation is analyzed. DG performance is assessed by comparative analysis with current techniques.

Sequence Component-Based Improved Passive Islanding Detection Method for Distribution System with Distributed Generations

2019 ◽  
Vol 20 (2) ◽  
Author(s):  
Bhatraj Anudeep ◽  
Paresh Kumar Nayak
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Low Cost ◽  
Rate Of Change ◽  
Islanding Detection ◽  
Detection Scheme ◽  
Small Power ◽  
Distributed Generations ◽  
Sequence Components ◽  
Detection Schemes

Abstract In distributed generation (DG) systems, the rate of change of voltage and the rate of change of frequency are the two most common and widely used simple and low-cost passive islanding detection schemes. Unfortunately, these passive islanding detection schemes find limitation for detecting the islandings that cause very small power imbalance. In this paper, an improved passive islanding detection scheme is proposed by using the two newly derived indices from the sequence components of the current signal with the conventional voltage and frequency parameters. The performance of the proposed scheme is tested for numerous islanding and non-islanding cases generated on IEEE Std 399–1997 and IEC microgrid model distribution system integrated with both inverter-interfaced and synchronous DGs through PSCAD/EMTDC. The obtained results confirm the effectiveness of the proposed scheme.

scholarly journals A Nondestructive Islanding Detection Method Based on Adaptive and Periodic Disturbance on Reactive Power Output of Inverter-Based Distributed Generation

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaolong Chen ◽  
Yongli Li
Keyword(s):  
Distributed Generation ◽  
Power Output ◽  
Reactive Power ◽  
Detection Method ◽  
Test System ◽  
Rate Of Change ◽  
Islanding Detection ◽  
Unity Power Factor ◽  
Periodic Disturbance ◽  
Strategy Transformation

In order to detect islanding nondestructively, an islanding detection method for microgrid is proposed based on adaptive and periodic disturbance on the reactive power output of inverter-based distributed generation (DG). The first two parts of the disturbance in a cycle form a symmetric triangular shape and the disturbance can adaptively adjust its peak value and cycle time for two purposes. One is to minimize the total amount of the disturbance. The other is to guarantee that the absolute value of the rate of change of frequency (ROCOF) is constant during islanding, which can be utilized to be a criterion to detect islanding. The method can be applied on the DG either operating at a unity power factor or generating both active and reactive power simultaneously. Moreover, it helps to avoid the serious transient process during control strategy transformation of the DG for microgrid islanded operation. According to the anti-islanding test system in the IEEE Std. 929-2000 and IEEE Std. 1547-2003, several study cases are carried out in the PSCAD/EMTDC environment. The simulation results show that the proposed method can detect islanding rapidly and nondestructively. Moreover, it also performs effectively for the system with multiple DGs.

scholarly journals Islanding Detection in Distributed Generation Integrated Thimi – Sallaghari Distribution Feeder Using Wavelet Transform and Artificial Neural Network

2019 ◽  
Vol 15 (2) ◽  
pp. 55-61
Author(s):  
Basanta Pancha ◽  
Rajendra Shrestha ◽  
Ajay Kumar Jha
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wavelet Transform ◽  
Power Quality ◽  
Distributed Generation ◽  
Reactive Power ◽  
External Signal ◽  
Islanding Detection ◽  
Detection Zone ◽  
Artificial Neural

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.

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