Probabilistic assessment of operational risk considering different wind turbine technologies

This paper presents an assessment of the variability on the output power of three different types of wind turbines commercially available. The dynamic response of terminal voltage, active power and reactive power are evaluated using time-domain simulations obtained from DIgSILENT® PowerFactory™. The assessment of the variability is performed based on probability density function, Pearson correlation coefficient and scatterplots. Results of this evaluation demonstrated that variable speed wind turbines using synchronous generator exhibits the better dynamic performance considering the wind speed changes, and highlight the need of smart grid oriented control strategies aiming at coordinated management of individual wind turbine controllers to avoid adverse implications of wind speed fluctuation.

[1]  F. Blaabjerg,et al.  Flicker study on variable speed wind turbines with doubly fed induction generators , 2005, IEEE Transactions on Energy Conversion.

[2]  Jacob Østergaard,et al.  On Small-Signal Stability of Wind Power System with Full-Load Converter Interfaced Wind Turbines , 2010 .

[3]  Yang Wang,et al.  Evaluation the effect of voltage sags due to grid balance and unbalance faults on DFIG wind turbines , 2009, 2009 International Conference on Sustainable Power Generation and Supply.

[4]  J. Morren,et al.  Short-Circuit Current of Wind Turbines With Doubly Fed Induction Generator , 2007, IEEE Transactions on Energy Conversion.

[5]  J. G. Slootweg,et al.  Representing wind turbine electrical generating systems in fundamental frequency simulations , 2003 .

[6]  H. Polinder,et al.  General Model for Representing Variable-Speed Wind Turbines in Power System Dynamics Simulations , 2002, IEEE Power Engineering Review.

[7]  T. Thiringer,et al.  Grid disturbance response of wind turbines equipped with induction generator and doubly-fed induction generator , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[8]  M. S. El-Moursi,et al.  Fault ride through capability enhancement for self-excited induction generator-based wind parks by installing fault current limiters , 2011 .

[9]  Henk Polinder,et al.  Dynamic modelling of a wind turbine with doubly fed induction generator , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[10]  V. Vittal,et al.  Impact of Increased Penetration of DFIG-Based Wind Turbine Generators on Transient and Small Signal Stability of Power Systems , 2010, IEEE Transactions on Power Systems.

[11]  Vijay Vittal,et al.  Impact of increased penetration of DFIG based wind turbine generators on transient and small signal stability of power systems , 2009, IEEE PES General Meeting.

[12]  S. M. Islam,et al.  Impacts of Symmetrical and Asymmetrical Voltage Sags on DFIG-Based Wind Turbines Considering Phase-Angle Jump, Voltage Recovery, and Sag Parameters , 2011, IEEE Transactions on Power Electronics.

[13]  Sebastian Achilles,et al.  Direct Drive Synchronous Machine Models for Stability Assessment of Wind Farms , 2003 .

[14]  Yang Wang,et al.  Voltage-Sag Tolerance of DFIG Wind Turbine With a Series Grid Side Passive-Impedance Network , 2010, IEEE Transactions on Energy Conversion.

[15]  Nicholas Jenkins,et al.  Comparison of fixed speed and doubly-fed induction wind turbines during power system disturbances , 2003 .

[16]  Stavros A. Papathanassiou,et al.  Dynamic behavior of variable speed wind turbines under stochastic wind , 1999 .

[17]  F. González-Longatt.  Influence of Turbulence on Power Quality : Comparative study between Constant and Variable Wind Turbines , 2008 .

[18]  F.D. Kanellos,et al.  Wind Farms Modeling for Short-Circuit Level Calculations in Large Power Systems , 2009, IEEE Transactions on Power Delivery.

[19]  Thomas Ackermann,et al.  Wind Power in Power Systems , 2005 .

[20]  Olimpo Anaya-Lara,et al.  Wind Energy Generation: Modelling and Control , 2009 .