Operations of Doubly Fed Induction Generators Applied in Green Energy Systems

Green Energy ◽  
2020 ◽  
pp. 495-514
Author(s):  
Bhagwan Shree Ram ◽  
Suman Lata Tripathi
Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4461
Author(s):  
Ahsanullah Memon ◽  
Mohd Wazir Mustafa ◽  
Muhammad Naveed Aman ◽  
Mukhtar Ullah ◽  
Tariq Kamal ◽  
...  

Brushless doubly-fed induction generators have higher reliability, making them an attractive choice for not only offshore applications but also for remote locations. These machines are composed of two back-to-back voltage source converters: the grid side converter and the rotor side converter. The rotor side converter is typically used for reactive current control of the power winding using the control winding current. A low voltage ride through (LVRT) fault is detected using a hysterisis comparison of the power winding voltage. This approach leads to two problems, firstly, the use of only voltage to detect faults results in erroneous or slow response, and secondly, sub-optimal control of voltage drop because of static reference values for reactive current compensation. This paper solves these problems by using an analytical model of the voltage drop caused by a short circuit. Moreover, using a fuzzy logic controller, the proposed technique employs the voltage frequency in addition to the power winding voltage magnitude to detect LVRT conditions. The analytical model helps in reducing the power winding voltage drop while the fuzzy logic controller leads to better and faster detection of faults, leading to an overall faster response of the system. Simulations in Matlab/Simulink show that the proposed technique can reduce the voltage drop by up to 0.12 p.u. and result in significantly lower transients in the power winding voltage as compared to existing techniques.


2014 ◽  
Vol 494-495 ◽  
pp. 1820-1824
Author(s):  
Dong Ning Wei ◽  
Xue Min Zhang ◽  
Jian Min Ye

In this paper, a novel modelling approach based on characteristic fusion is proposed and used to build a static equivalent model of wind farm. Firstly, the modelling framework based on characteristic fusion is given. Secondly, the basic characteristics of wind farm including characteristic of wind turbine generator (WTG), wind speed spatial distribution and characteristic of wind farm are analyzed according to the framework. Then detailed modelling process is provided utilizing SVR as a fusion tool. This approach combines the advantages of both mechanism and non-mechanism methods with both satisfactory fitting ability and generalization ability. It only requires the maximum and minimum value of wind speed among the wind farm, rather than accurate wake model as mechanism method nor massive measurement data as non-mechanism method. Numerical simulation indicates the effectiveness and robustness of the proposed method. When available data is reduced or includes bad measurement, the proposed method can still keep favorable performance.


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