Virtual Synchronous Generator Control of Power System Including Large Wind Farm by using HVDC Interconnection Line

2020 ◽  
Vol 140 (2) ◽  
pp. 104-110 ◽  
Author(s):  
Sho Niino ◽  
Atsushi Umemura ◽  
Rion Takahashi ◽  
Junji Tamura ◽  
Yoshiharu Matsumura ◽  
...  
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.


2014 ◽  
Vol 1070-1072 ◽  
pp. 193-199
Author(s):  
Min Jiang Chen ◽  
Yue Qing Chen ◽  
Wang Chao Dong ◽  
Bei Wu

This paper uses the optimal probabilistic load flow method for power containing wind farm analysis. Based on Computation of optimal load flow using the Interior point method ,considering the stochasticlal power output of wind generator and the random outage of synchronous generator and the stochastic of load power, calculating the probability distribution of branch power flow and node voltage. This paper uses RTS-24 as the example to analysis the method ,and comparison the results with that of the Monte-Carlo method, to analysis the change of power system after the grid connected of wind turbine.


Sign in / Sign up

Export Citation Format

Share Document