Transient stability of induction generators in wind farm applications

Author(s):  
Mirza Saric ◽  
Irfan Penava

Low voltage ride through capability is an ability of the wind farm to stay connected with grid at the time of disturbance in the power system. The penetration of wind based renewable energy resources is increasing and the low voltage ride through consideration is vital for systems studies. The literature available demonstrates the improvement in low voltage ride through either by using fault current limiters or by implementing a control strategy for induction generator based wind farms. In this paper the low voltage ride through capability enhancement of the fixed speed induction generator is presented with various fault current limiters. The authors have presented the effects of fault current limiters in the aggregated hybrid wind farm consisting the combination of fixed speed induction generators and doubly fed induction generators which is not available in literature so far. A transient fault is simulated using PSCAD/EMTDC software in both the cases and the results are presented and discussed.


2021 ◽  
Vol 2120 (1) ◽  
pp. 012023
Author(s):  
Brish Ramlochun ◽  
Chockalingam Aravind Vaithilingam ◽  
Ahmad Adel Alsakati ◽  
Jamal Alnasseir

Abstract Electricity is in high demand with a fast-growing population; hence it is advisable to turn towards green energy. In this research, Wind Turbine (WT) is modelled with two different types of induction generators (IGs), which are the Doubly-Fed Induction Generator (DFIG) and Squirrel-Cage Induction Generator (SCIG) and implemented to IEEE 9-Bus system to assess the transient stability. MATLAB/ Simulink R2019a platform was considered to carry the whole examination. DC1A excitation system was applied to Synchronous Generators (SGs) as well as Power System Stabilizer (PSS). The transmission line7-5 was found to suffer from a high peak value of a relative power angle of approximately 130 degrees. As for the settling time, without PSS it was 20.69 s and with PSS it became 6.23 s. A wind farm with a rated capacity of 60 MW was used in the system. WT integrated with DFIG has the lowest peak value of 127 degrees at Bus locations 4 and 5 and for SCIG, Bus 5 with a peak value of 136 degrees. Thus, it can be propelled as the perfect location. Moreover, this is due to the three-phase fault was located at the transmission line7-5 which is far away from Buses 4 and 5. In the end, the WT integrated with DFIG provides a lower peak value of relative power angle compared to SCIG, whereas for settling time, it is the opposite.


2011 ◽  
Vol 347-353 ◽  
pp. 791-794 ◽  
Author(s):  
Xiao Yan Bian ◽  
Guang Yue Li ◽  
Yang Fu

It’s a new challenge to power system stability with large wind farm’s integration. Taking the wind farm which consist of GE1.5MW double fed induction generators that has been modeled in the software PSS/E as the research object, The difference between the impact of wind farm and conventional generators integrated to grid in power system transient progress is analyzed. Besides, the impact on transient progress of increasing wind farm penetration and differnet interconnection with wind farm to power system is investigated.


Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.


2013 ◽  
Vol 805-806 ◽  
pp. 334-337
Author(s):  
Shi Wei Su ◽  
You Wei Zhou ◽  
Wei Xiong

Analysis compares the direct access to a single set of wind power systemTwo groups of wind farm access system directlyMultiple sets of wind farm access system directly And Multiple sets of wind dispersion access system's impact on power system transient stability. And compare the simulation results, Concluded that wind farm access capacity and its topology structure's influence on system transient stability.


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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