New Islanding Detection Method With Voltage Amplitude Variation for Inverter-based Distributed Generator

Author(s):  
Kianoush Naraghipour ◽  
Khaled Ahmed ◽  
Campbell Booth
2013 ◽  
Vol 846-847 ◽  
pp. 750-755
Author(s):  
Wen Huang ◽  
Tao Zheng ◽  
Shi Guang Xu ◽  
Zhi Yuan Liu ◽  
Jing Hua Wen

Active frequency drift islanding detection method is one of most widely used in the distributed generator islanding detection. Now domestic researches of islanding detection have not been done deep researched about the reason why islanding detection method will become invalid. Therefore, the paper analyses the performances of the frequency drift islanding method from load phase frequency characteristic and algorithm phase frequency characteristic, which are the major factors affecting the effectiveness of islanding detection method. At last, this paper proved the analysis results with MATLAB.


Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 506 ◽  
Author(s):  
Kuang-Hsiung Tan ◽  
Chien-Wu Lan

In this study, an intelligent controlled distributed generator (DG) system is proposed for tracking control and islanding detection. First, a DC/AC inverter with DC power supply is adopted to emulate a DG system and control the active and reactive power outputs. Moreover, in order to comply with the standard for interconnection with the power grid, a novel active islanding detection method is proposed for the inverter-based DG system. In the proposed active islanding detection method, a perturbation signal is designed to inject into the d-axis current of the DG system which causes the frequency at the terminal of the RLC load to deviate when the power grid breaks down. The feasibility of the proposed active islanding detection method is verified according to the UL 1741 test configuration. Furthermore, in order to improve the tracking control of the active and reactive powers of the inverter-based DG system, and to effectively reduce the detection time of islanding phenomenon, two probabilistic fuzzy neural network (PFNN) controllers are adopted to take the place of the conventional proportional-integral (PI) controllers. In addition, the network structure and the online learning algorithm of the adopted PFNN are presented in details. Finally, some experimental results of the proposed active islanding detection method using PFNN controllers are proposed to validate the effectiveness and feasibility of the tracking control and islanding detection.


2017 ◽  
Vol 8 (4) ◽  
pp. 1821-1830 ◽  
Author(s):  
Qinfei Sun ◽  
Josep M. Guerrero ◽  
Tianjun Jing ◽  
Juan C. Vasquez ◽  
Rengang Yang

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Manop Yingram ◽  
Suttichai Premrudeepreechacharn

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.


Solar Energy ◽  
2013 ◽  
Vol 97 ◽  
pp. 155-167 ◽  
Author(s):  
Ku Nurul Edhura Ku Ahmad ◽  
Nasrudin Abd Rahim ◽  
Jeyraj Selvaraj ◽  
Ahmad Rivai ◽  
Krismadinata Chaniago

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