Validation of Passive Islanding Detection Methods for Double Line-to-Ground Unsymmetrical Fault in a Three-Phase Microgrid System

2021 ◽  
Author(s):  
Bangar Raju Lingampalli ◽  
◽  
K. Subba Rao ◽  
Keyword(s):  
Detection Methods ◽  
Islanding Detection ◽  
Double Line ◽  
Three Phase

scholarly journals Comparative Study of Different Approaches for Islanding Detection of Distributed Generation Systems

2019 ◽  
Vol 2 (3) ◽  
pp. 25 ◽  
Author(s):  
Ashish Shrestha ◽  
Roshan Kattel ◽  
Manish Dachhepatic ◽  
Bijen Mali ◽  
Rajiv Thapa ◽  
...  
Keyword(s):  
Decision Tree ◽  
Distributed Generation ◽  
Distribution System ◽  
Short Circuit ◽  
Distribution Networks ◽  
Detection Methods ◽  
Islanding Detection ◽  
Detection Zone ◽  
Three Phase ◽  
Typical Distribution

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.

scholarly journals Over/Undervoltage and Undervoltage Shift of Hybrid Islanding Detection Method of Distributed Generation

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Manop Yingram ◽  
Suttichai Premrudeepreechacharn
Keyword(s):  
Control System ◽  
Distributed Generation ◽  
Hybrid Method ◽  
Detection Method ◽  
System Simulation ◽  
Detection Methods ◽  
Islanding Detection ◽  
Active Method ◽  
Passive Method ◽  
Simulation Results

The mainly used local islanding detection methods may be classified as active and passive methods. Passive methods do not perturb the system but they have larger nondetection zones, whereas active methods have smaller nondetection zones but they perturb the system. In this paper, a new hybrid method is proposed to solve this problem. An over/undervoltage (passive method) has been used to initiate an undervoltage shift (active method), which changes the undervoltage shift of inverter, when the passive method cannot have a clear discrimination between islanding and other events in the system. Simulation results on MATLAB/SIMULINK show that over/undervoltage and undervoltage shifts of hybrid islanding detection method are very effective because they can determine anti-islanding condition very fast.ΔP/P>38.41% could determine anti-islanding condition within 0.04 s;ΔP/P<-24.39% could determine anti-islanding condition within 0.04 s;-24.39%≤ΔP/P≤ 38.41% could determine anti-islanding condition within 0.08 s. This method perturbed the system, only in the case of-24.39% ≤ΔP/P ≤38.41% at which the control system of inverter injected a signal of undervoltage shift as necessary to check if the occurrence condition was an islanding condition or not.

scholarly journals Study of Harmonic Detection Methods under Non-Ideal Conditions in Ship Power Network

2015 ◽  
Vol 22 (3) ◽  
pp. 82-89
Author(s):  
Xiao-Yan Xu ◽  
Janusz Mindykowski ◽  
Tomasz Tarasiuk ◽  
Chen Cheng
Keyword(s):  
Phase Lock Loop ◽  
Mean Value ◽  
Detection Methods ◽  
Harmonic Detection ◽  
Phase Voltage ◽  
Rapid Variation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Three Phase ◽  
In Series

Abstract An improved harmonic detection method based on average arithmetic is proposed. According to the research results, the designed solution uses an LPF (low-pass-filter) and a mean value module connected in series instead of the conventional mean value module, and simultaneously, a three-phase voltage phase-locked module instead of commonly used PLL (phase lock loop) module is applied in order to reduce the influence caused by three-phase distorted voltage and rapid variation of load. The experimental results show that the application of this solution leads to increase in the accuracy of harmonics detection for distorted three-phase voltage and rapid variation of load.

scholarly journals Diagnosis of the Induction Machine Using Advanced Signal Processing Methods

2018 ◽  
Vol 3 (3) ◽  
pp. 143-150
Author(s):  
Abdelghani CHAHMI
Keyword(s):  
Induction Machine ◽  
Detection Methods ◽  
Diagnostic Tools ◽  
Simulation Tools ◽  
Electric Drives ◽  
Efficient Simulation ◽  
Squirrel Cage ◽  
Rotor Resistance ◽  
Three Phase ◽  
Signal Processing Methods

This work is a part of the thematic of monitoring and fault diagnosis of the squirrel cage three-phase induction machine. The choice of this type of machine is justified by the growing success it has exhibited, mainly, in the electric drives with variable speed. Signal based detection methods are presented is validated in simulation. The proposed diagnosis approach requires only little experimental data, and more importantly it provides efficient simulation tools that allow characterizing faulty behavior.In this study, the proposed approach considers the value of rotor resistance as fixed for condition monitoring. This value in the diagnostic tools which one uses is not fixed contrary to the classical approaches of control of machine.

scholarly journals A Test Device for Optimize PMU-Based Islanding Detection Technology

2015 ◽  
Vol 10 (2) ◽  
Keyword(s):  
Power Systems ◽  
Power Plants ◽  
Detection Method ◽  
Detection Methods ◽  
Islanding Detection ◽  
Algorithm Optimization ◽  
Test Device ◽  
Photovoltaic Power ◽  
Detection Technology ◽  
Bulk Power

Islanding detection is a necessary function for grid connected distributed generators. Usually, islanding detection methods can be classified as two catalogues: remote detecting methods and local detecting methods. Most of them have limitation and defects when they are applied in photovoltaic power stations. Recently synchronous phasor measuring units (PMU) is proposed to be applied for islanding detecting. Although the islanding detection method is supposed to be applied for traditional bulk power systems, it is also suitable for renewable generation power plants. To do this islanding detection will be implemented on central management unit of photovoltaic power station instead of on grid-tied inverters as traditionally. In implementing, the criteria of this method and the threshold of algorithm are needed to be optimized. This paper develops a test device which can optimize PMU-based islanding detection technology to validate the proposed islanding detection method applying in PV station. Then using simulation to discuss how to set a reasonable threshold for the researched islanding detection method applied in PV stations. Finally the paper provides a platform for the algorithm optimization.

scholarly journals Intelligent Islanding Detection of Microgrids Using Long Short-Term Memory Networks

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5762
Author(s):  
Syed Basit Ali Bukhari ◽  
Khawaja Khalid Mehmood ◽  
Abdul Wadood ◽  
Herie Park
Keyword(s):  
Short Term Memory ◽  
Computational Time ◽  
Islanding Detection ◽  
Phase Voltage ◽  
Short Term ◽  
Term Memory ◽  
Three Phase ◽  
Empirical Wavelet Transform ◽  
Long Short Term Memory ◽  
Lstm Network

This paper presents a new intelligent islanding detection scheme (IIDS) based on empirical wavelet transform (EWT) and long short-term memory (LSTM) network to identify islanding events in microgrids. The concept of EWT is extended to extract features from three-phase signals. First, the three-phase voltage signals sampled at the terminal of targeted distributed energy resource (DER) or point of common coupling (PCC) are decomposed into empirical modes/frequency subbands using EWT. Then, instantaneous amplitudes and instantaneous frequencies of the three-phases at different frequency subbands are combined, and various statistical features are calculated. Finally, the EWT-based features along with the three-phase voltage signals are input to the LSTM network to differentiate between non-islanding and islanding events. To assess the efficacy of the proposed IIDS, extensive simulations are performed on an IEC microgrid and an IEEE 34-node system. The simulation results verify the effectiveness of the proposed IIDS in terms of non-detection zone (NDZ), computational time, detection accuracy, and robustness against noisy measurement. Furthermore, comparisons with existing intelligent methods and different LSTM architectures demonstrate that the proposed IIDS offers higher reliability by significantly reducing the NDZ and stands robust against measurements uncertainty.

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