scholarly journals Laboratory Evaluation of Phasor Based Islanding Detection Method

Author(s):  
Szymon Barczentewicz ◽  
Andrzej Bien ◽  
Tomasz Lerch ◽  
Krzysztof Duda
Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1953
Author(s):  
Szymon Barczentewicz ◽  
Tomasz Lerch ◽  
Andrzej Bień ◽  
Krzysztof Duda

Constantly growing distributed energy generation based on renewable sources creates a number of new challenges for electrical power system operation. One of the challenges is islanding detection. Unintentional islanding, which can cause health and safety hazards for the personnel, is currently being experienced by a growing number of consumers/prosumers especially in the case of photovoltaic inverters. This work presents a new islanding detection method based on synchrophasor measurements. The proposed method works in either a passive or hybrid mode. In a passive mode, a single phasor measurement unit (PMU) in the island region is used. In a hybrid mode, one PMU in the island and another one outside the island are exploited. The proposed method was verified in conducted laboratory tests that confirmed the applicability of PMUs data for effective detection and monitoring of unintentional islanding.


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

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.


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