LOGO Meng Wu 1 , Rongfu Sun 2 , Lin Cheng 3 , and Le Xie 1 1: Texas A&M University, 2: China Jibei Power Grid, 3: Tsinghua University 10-21-2014 Parameter Sensitivity Analysis for Sub-Synchronous Oscillations in Wind-Integrated Power Systems
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LOGO
Meng Wu1, Rongfu Sun2, Lin Cheng3, and Le Xie1
1: Texas A&M University, 2: China Jibei Power Grid, 3: Tsinghua University
10-21-2014
Parameter Sensitivity Analysis for Sub-Synchronous Oscillations in Wind-Integrated Power Systems
Wind Farm SSO Events in Real World
2
Wind Farm SSO in Real World
In Oct. 2009, ERCOT reported a SSO in wind-integrated system, triggered by a single line-to-ground fault.
A NREL report in 2013 presents several SSO incidents recorded by wind power plants of Oklahoma Gas & Electric Company.
China Jibei Power Grid also encounters SSO induced by wind power integration.
Y. H. Wan, “Synchronized phasor data for analyzing wind power plant dynamic behavior and model validation”, 2013. P. Belkin, “Event of 10-22-09”, in CREZ Technical Conference, 2010.
Basic Characteristics of Wind Farm SSO
3
Characteristics of Wind Farm SSO
Electrical oscillation typically in the frequency range of 20 – 50 Hz.
Caused by interactions among wind generators, controllers of power electronic devices, and series compensated network.
Can be difficult to filter since the oscillation frequency may be close to synchronous frequency.
DFIG-based wind turbine are most sensitive to SSO among all kinds of wind turbines.
Garth Irwin, “Sub-synchronous control interaction studies related to the CREZ project”, 2010
How to Deal With Wind Farm SSO?
4
Wind Farm SSO Phenomenon Identify Root Cause Identify Critical
Parameters& Inputs
Verification Through Simulation
Sensitivity-Based Mitigation Control
• Small-signal instability induced by certain parameter settings and input conditions
• Eigenvalue sensitivities with respect to system parameters & input conditions
• Sensitivity-based optimal parameter adjustment for wind farm SSO mitigation
Wind Farm SSO Can Be
Eliminated Effectively
Wind Farm SSO vs Parameters & Inputs
5
Small-Signal Stability
Study eigenvalues of A matrix: negative real part -> stable positive real part -> unstable
A matrix of the linearized system can be expressed as
function of ONLY system parameters & inputs
Wind SSO Stability
Small Signal stability of Wind Farm SSO is determined by ONLY
system parameters & inputs
System Nonlinear Model
System Linearized Model
Linearized State Matrix
How to Deal With Wind Farm SSO?
6
Wind Farm SSO Phenomenon Identify Root Cause Identify Critical
Parameters& Inputs
Verification Through Simulation
Sensitivity-Based Mitigation Control
• Small-signal instability induced by certain parameter settings and input conditions
• Eigenvalue sensitivities with respect to system parameters & input conditions
• Sensitivity-based optimal parameter adjustment for wind farm SSO mitigation
Wind Farm SSO Can Be
Eliminated Effectively
Eigenvalue Analysis – Low Wind Speed
7
System Condition
Steady-State Infinite Bus |V| = 1 pu
Steady-State Infinite Bus θ = 0 rad
Steady-State DFIG Pout = 1 pu
Steady-State DFIG Power Factor = 0.9
Wind Speed = 4 m/s
Series Compensation Level = 52.38%
5 oscillation modes in total: 3 sub-synchronous and 2 super-synchronous
22.06 Hz sub-synchronous mode is unstable in low wind speed condition.
The other two sub-synchronous modes are stable with small damping compared with super-synchronous modes.
Sensitivity Analysis for SSO Modes
8
D K Jw Jg Xls Xm Xlr Rs Rr Rnt Lnt Cnt Xxf Kte Tte Kiqr Tiqr Kqs Tqs Kidr Tidr Kqg Tqg KiqgTiqg Kdc Tdc KidgTidg Cdc-0.1
0
0.1
System Parameters
D K Jw Jg Xls Xm Xlr Rs Rr Rnt Lnt Cnt Xxf Kte Tte Kiqr Tiqr Kqs Tqs Kidr Tidr Kqg Tqg KiqgTiqg Kdc Tdc KidgTidg Cdc-0.1
0
0.1
System Parameters
D K Jw Jg Xls Xm Xlr Rs Rr Rnt Lnt Cnt Xxf Kte Tte Kiqr Tiqr Kqs Tqs Kidr Tidr Kqg Tqg KiqgTiqg Kdc Tdc KidgTidg Cdc-0.01
0
0.01
System Parameters
Wr Pe Qe Eq Ed Vdc-1
-0.5
0
0.5
Operating Conditions
Wr Pe Qe Eq Ed Vdc-0.1
0
0.1
0.2
0.3
Operating Conditions
Wr Pe Qe Eq Ed Vdc-4
-2
0
2
4x 10-3
Operating Conditions
Eigenvalue Sensitivities for 22.06 Hz Mode
Eigenvalue Sensitivities for 8.09 Hz Mode
Eigenvalue Sensitivities for 1.27 Hz Mode
Torsional System
DFIG System
Network System
Operating Conditions
Controller System
Sensitivity Analysis for SSO Modes
9
22.06 Hz mode is sensitive to network parameters and DFIG converter controller parameters.
8.09 Hz mode is sensitive to DFIG parameters and network parameters.
1.27 Hz mode is sensitive to torsional system parameters, network parameters and controller parameters.
Network inductor and capacitor values are of high sensitivities in all three sub-synchronous modes.
Parameters in current control loops of converter controllers have higher sensitivities over torque control loops.
DFIG rotor speed (determined by wind speed) has significant influence on all three modes.
0 5 10 15 20 25 300
50
100
150
200
250
300
350
400
450
Wind Speed (m/s)
DFI
G R
otor
Spe
ed (r
ad/s
)
DFIG Rotor Speed at Different Wind SpeedSystem Synchronous Speed
How to Deal With Wind Farm SSO?
10
Wind Farm SSO Phenomenon Identify Root Cause Identify Critical
Parameters& Inputs
Verification Through Simulation
Sensitivity-Based Mitigation Control
• Small-signal instability induced by certain parameter settings and input conditions
• Eigenvalue sensitivities with respect to system parameters & input conditions
• Sensitivity-based optimal parameter adjustment for wind farm SSO mitigation
Wind Farm SSO Can Be
Eliminated Effectively
Simulation Results Before Parameter Adjustment
11
0 1 2 3 4
-0.2
-0.1
0
0.1
0.2
0.3
Time (s)
Transmission Line Current (pu)
0 20 40 60 80 1000
0.02
0.04
0.06
0.08
0.1
0.12
Frequency (Hz)
FFT Analysis of Line Current
0 1 2 3 4-0.4
-0.3
-0.2
-0.1
0
0.1
Time (s)
DFIG Electrical Torque (pu)
0 10 20 30 40 500
0.02
0.04
0.06
0.08
0.1
Frequency (Hz)
FFT Analysis of DFIG Electrical Torque
Oscillation frequency of transmission line current: 27.92 Hz
Oscillation frequency of DFIG electrical torque: 22.13 Hz
Simulation Results Before Parameter Adjustment
12
0 1 2 3 4-0.2
-0.1
0
0.1
0.2
Time (s)
Transmission Line Current (pu)
0 20 40 60 80 1000
0.02
0.04
0.06
0.08
0.1
0.12
Frequency (Hz)
FFT Analysis of Line Current
-
-
-
-
-
0
0 1 2 3 4-0.136
-0.135
-0.134
-0.133
-0.132
DFIG Electrical Torque (pu)
0 10 20 30 40 500
0.02
0.04
0.06
0.08
0.1
Frequency (Hz)
FFT Analysis of DFIG Electrical Torque (p
Sensitive gains of converter controller are adjusted.
Unstable eigenvalues are moved left effectively.
Gain of GSC current control loop (Kiqg) is tuned for SSO mitigation from 1.0 to 0.5
Conclusions
13
Conclusions
What Happened: Sub-synchronous oscillation happens in wind-integrated power system.
Why It Occurred: Inappropriate operating conditions, series-compensated network parameters as well as DFIG converter controller parameters .
How To Eliminate: Eigenvalue adjustment based on sensitivity analysis and parameter tuning (including DFIG converter controller gains and network compensation level).
Future Work
Extend sensitivity analysis to multi-machine systems.
Design optimal mitigation control strategies for wind farm SSO.
References
14
References
[1] Y. H. Wan, “Synchronized phasor data for analyzing wind power plant dynamic behavior and model validation”, National Renewable Energy Laboratory, CO, Tech. Rep. NREL/TP-5500-57342, Jan 2013.
[2] P. Belkin, “Event of 10-22-09”, in CREZ Technical Conference, Jan 2010.
[3] Z. Lubosny, Wind Turbine Operation in Electric Power Systems: Advanced Modeling. Berlin, Germany: Springer-Verlag, 2003.
[4] P. C. Krause, O. Wasynczuk, and S. D. Sudhoff, Analysis of Electric Machinery. NY: IEEE Press, 1995.
[5] P. M. Anderson, B. L. Agrawal, and J. E. Van Ness, Subsynchronous Resonance in Power Systems. NY: IEEE Press, 1990.
[6] M. Wu, R. Sun, L. Cheng, and L. Xie, “Parameter sensitivity analysis for sub-synchronous control interactions in wind-integrated power systems”, submitted to CIGRE Grid of the Future Symposium, 2014, Houston, TX, Oct 2014
LOGO
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