Hybrid islanding detection method by virtual synchronous generator in micro-grids with flexible DG

Author(s):  
A. Azizi ◽  
S. M. T. Bathaee
Author(s):  
Illuru Sree Lakshmi

Abstract: An islanding detection and based control strategy is created in this exploration to accomplish the steady and independent activity of microgrids using the neural network based Virtual Synchronous Generator (VSG) idea during unplanned grid reconfigurations . Maybe of utilizing a design-orientedmethodology, this paper gives a rigorous and extensive hypothetical investigation and reaches a concise conclusion that is easy to execute and successful even in complex situations. Based on the results of the mutation sequence and voltage wavering, a neural network based islanding identification calculation is proposed, which requires less constraint strategy. The proposed neural network approach outperforms the thefrequency measured passive detection method in terms of detection speed and reliability. Broad recreations affirm the reasonableness of the proposed islanding location and control methodology. Additionally, think about the results of the reproductions for the PI regulator, fluffy organizations, and neural organizations. Keywords: Virtual Synchronous Generator, Islanding detection, Islanding operation, Droop control, Stability, Microgrids.


2017 ◽  
Vol 137 (6) ◽  
pp. 546-552 ◽  
Author(s):  
Yuko Hirase ◽  
Osamu Noro ◽  
Shogo Katsura ◽  
Kensho Abe ◽  
Eiji Yoshimura ◽  
...  

2020 ◽  
Vol 140 (6) ◽  
pp. 531-538
Author(s):  
Kotaro Nagaushi ◽  
Atsushi Umemura ◽  
Rion Takahashi ◽  
Junji Tamura ◽  
Atsushi Sakahara ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4581
Author(s):  
Yuko Hirase ◽  
Yuki Ohara ◽  
Naoya Matsuura ◽  
Takeaki Yamazaki

In the field of microgrids (MGs), steady-state power imbalances and frequency/voltage fluctuations in the transient state have been gaining prominence owing to the advancing distributed energy resources (DERs) connected to MGs via grid-connected inverters. Because a stable, safe power supply and demand must be maintained, accurate analyses of power system dynamics are crucial. However, the natural frequency components present in the dynamics make analyses complex. The nonlinearity and confidentiality of grid-connected inverters also hinder controllability. The MG considered in this study consisted of a synchronous generator (the main power source) and multiple grid-connected inverters with storage batteries and virtual synchronous generator (VSG) control. Although smart inverter controls such as VSG contribute to system stabilization, they induce system nonlinearity. Therefore, Koopman mode decomposition (KMD) was utilized in this study for consideration as a future method of data-driven analysis of the measured frequencies and voltages, and a frequency response analysis of the power system dynamics was performed. The Koopman operator is a linear operator on an infinite dimensional space, whereas the original dynamics is a nonlinear map on a finite state space. In other words, the proposed method can precisely analyze all the dynamics of the power system, which involve the complex nonlinearities caused by VSGs.


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