Impact of increased wind power generation on subsynchronous resonance of turbine-generator units
With more and more wind power generation integrated into power grids to replace the conventional turbine-generator (T-G) units, how the subsynchronous resonance (SSR) of conventional T-G units is affected becomes an important technical issue. In this paper, a group of T-G units are interconnected with a series compensated transmission line, and some units are substituted by a nearby DFIG-based wind farm (WF). Under such circumstances, the SSR of power systems would change accordingly. This paper establishes the mathematical model to analyze the torsional interaction (TI) and the induction generator effect of the T-G units. Both eigenvalue analysis and time domain simulations demonstrate the impact of DFIG-based WF on SSR of power systems and how the control parameters of wind farms can affect the SSR.
KeywordsSubsynchronous resonance (SSR) Doubly fed induction generator (DFIG) Torsional interaction (TI) Induction machine effect (IGE)
Series capacitive compensation is widely utilized to increase the capacity of the transmission line. However, the potential risk of the series capacitive compensation is that it may cause the subsynchronous resonance (SSR). Basically, the SSR interaction is divided into three categories: torsional interaction (TI), induction generator effect (IGE) and torsional amplification (TA) [1, 2]. The TI involves the mechanical system of a turbine-generator (T-G) unit and the electrical system. It would happen when the complement of the natural frequency of the network is close or coincides with one of the torsional frequencies of the T-G shaft system . The IGE is purely an electrical phenomenon, and it depends on the generator and the electrical system. Both of the TI and IGE are related with steady state of power systems. The TA is nonlinear transient dynamics and will not be discussed in this paper. The SSR problem of the T-G units interconnected with a series compensated transmission line has been recognized for many years and extensively studied . However, the increased utilization of renewable energy may affect the SSR of T-G units.
Under the pressure of environmental protection, the sources of the electrical power gradually change from conventional fossil based sources to renewable energy resources. Until now, wind energy is the most widely utilized renewable energy around the world. In Demark, the penetration of wind energy has reached 12% in 2012, providing a substantial amount of the electricity demand . As the level of wind penetration increases, the dynamics of the conventional T-G units would significantly be influenced by large scale wind farms.
Due to its high capacity, low cost and flexible control, the doubly-fed induction generator (DFIG) is very popular among all the other types of wind generation . In North America, most large wind farms employ the DFIG-base wind turbines . Research papers investigated the impact of the DFIG-based wind farm on the small signal stability of power system [8, 9, 10]. The results of these publications concluded that the DFIG-based wind farms had both positive and negative effect on the electromechanical oscillations under different circumstances. On the other hand, the SSR of the DFIG-based wind farm has been studied [11, 12]. It was found that DFIG-based wind farm was very vulnerable to SSR, and the SSR was mainly attributed to the IGE instead of the TI. This conclusion was also confirmed by the SSR phenomenon in practical wind farms . Reference  presented the procedures to study the SSR in wind integrated power systems. Moreover, the DFIG-based wind farm was utilized to damp the torsional oscillations of the conventional T-G units [6, 7]. However, the above publications have not studied that the impacts of the DFIG-based wind farm on the SSR of conventional T-G units.
Thus, the contribution of this paper is to systematically investigate the impacts of the DFIG-based wind farm on the SSR of T-G units. The test benchmark is modified from the IEEE first benchmark model. The detailed model is established for the test system. The eigenvalue analysis and time domain simulation are conducted to examine the influence of wind farm on both TI and IGE of the T-G unit and how the control parameters of wind farms can affect the SSR.
This paper is organized as follows. In Section 2, the details of the studied test benchmark are introduced. Then, the detailed models for the T-G units, the DFIG-based wind turbine and the transmission line are presented in Section 3. Section 4 describes the eigenvalue analysis and time domain simulations of the studied system. The results of eigenvalue analysis and time domain simulations for both TI and IGE are demonstrated in Section 5 and 6. Section 7 summarizes this paper.
2 Test benchmark
The shaft system of the GEN 1 consists of six torsional masses: a high-pressure turbine section (HP), an intermediate-pressure turbine section (IP), two low-pressure turbine section (LPA and LPB), a rotor of generator (GEN) and a rotating exciter (EXC). Since six masses are considered in the shaft system, there are six modes of oscillation, named from Mode 0 to Mode 5. The Mode 0 represents the oscillation of the entire six masses against the power system, and it is often considered in system stability studies . The other five modes are the torsional oscillation modes, and their mode shapes can be found in . The compensation level of the transmission line tuned to excite Mode 2. Mode 2 has a natural frequency of 21.21 Hz, and it includes two polarity reversals according to the mode shapes. One polarity reversal happens between the LPA and LPB section, and the other one happens between the GEN and EXC section. So, in the time domain simulation, the excited oscillation of Mode 2 can be observed through the torsional response of LPA-LPB and GEN-EXC. The shaft system of the generators in GEN 2 is modeled as a lumped mass.
In this paper, the wind farm is supposed to replace conventional generators in GEN 2 gradually. The number of wind turbines in the aggregated wind farm will change to demonstrate the scenarios with different penetration level of wind energy. However, the overall power generated by GEN 2 and the DFIG-based wind farm will be kept unchanged at 750 MW. The power factor and output power of GEN 1 will be the same as in the IEEE FBM.
3 System modeling
The benchmark system has been introduced in previous part. In this part, every component of the benchmark system will be modeled separately for eigenvalue analysis.
3.1 Turbine-generator unit
1) Shaft system
The shaft system of GEN 2 only includes one lumped mass, and it also can be demonstrated by the above model accordingly.
2) Synchronous machine
3.2 DFIG-based wind turbine
1) Drive train
The drive train includes wind turbine, gearbox, shafts and other mechanical components, and it is usually represented by a two-mass model .
2) Induction generator
3) DC-link capacitor
4) Rotor and grid side converters
3.3 Transmission line
4 Eigenvalue analysis and time domain simulation
To evaluate the impact of increased wind energy on the SSR of the test benchmark, the eigenvalue analysis and time domain simulation are conducted in the following two cases.
Case 1: The test benchmark as Fig. 1 without the wind farm. The number of synchronous generators in GEN 2 is 10, and the output power of each one is 75 MW
Case 2: The test benchmark as Fig. 1. A certain number of power generators in GEN 2 are substituted by a DFIG-based wind farm with equivalent capacity.
4.1 Eigenvalue analysis
The state variable vector ΔXnet includes the d and q axis voltages of compensation capacitor.
Based on (14), the eigenvalues of Case 2 can be calculated according to the operating point and the parameters in Appendix A. As for Case 1, the eigenvalues can be obtained after removing the state variables of wind farm in ΔX1.
4.2 Time domain simulation
5 Results of torsional interaction
In this part, the DFIG-based wind farm will replace a certain number of generators in GEN 2 with equivalent capacity. The impact of this replacement on the torsional interaction of GEN 1 will be investigated.
In the test benchmark, the torsional oscillations of GEN 1 unit mainly depend on the compensation level of the transmission line and the dynamics of the wind farm. To excite the same mode of torsional oscillation, the compensation level remains the same in this part. The dynamics of the wind farm are attributed to three major factors: the scale of the wind farm, the control parameters and the operating point of wind generators. In the following studies, with the changes of these three factors, the effect of the wind farm on the torsional interaction of the GEN 1 is studied.
5.1 Impact of wind farm scale
The torsional mode of GEN 1 may change when some generators in GEN 2 is replaced by the increased wind farm. Initially, the DFIG-based wind farm is supposed to contain 100 wind turbines, and the output power of each wind turbine is 1.5 MW. Consequently, two 75 MW power generators in GEN 2 stop to produce power. Then, the number of DFIG-based wind turbines increases from 100 to 200, and the number of replaced generators in GEN 2 increases from 2 to 4.
Torsional Mode 2 under variable wind farm scale
Wind farmscale (MW)
Eigenvalue (Mode 2)
0.29 ± 127.95i
0.56 ± 127.84i
0.71 ± 127.17i
0.78 ± 127.19i
0.82 ± 127.21i
0.85 ± 127.23i
0.87 ± 127.25i
0.89 ± 127.26i
5.2 Impact of DFIG converter control
In this section, the impact of the DFIG converter control on the TI will be investigated. The number of the DFIG-based wind turbines is fixed at 100, and the output power of each wind turbine is still 1.5 MW.
Torsional Mode 2 under different control parameters
Control parameter Kp2
Eigenvalue (Mode 2)
0.56 ± 127.84i
0.51 ± 127.79i
0.45 ± 127.77i
0.41 ± 127.76i
0.39 ± 127.76i
5.3 Impact of operating points
Operating point of a DFIG-based wind turbine
Wind speed (m/s)
Output power (MW)
Torsional Mode 2 under variable operating point
Operating point (MW)
Eigenvalue (Mode 2)
0.42 ± 127.46i
0.46 ± 126.59i
0.50 ± 127.72i
0.56 ± 127.84i
6 Results of induction generator effect
For this part of study, the induction machine effect of the test benchmark is analyzed when some generators in GEN 2 are substituted by a DFIG-based wind farm. To focus on the IGE, the torsional dynamics of GEN 1 are disabled in both eigenvalue analysis and time domain simulation. The resistance of the series compensated transmission line RTL is reduced to 0.00645 to excite the IGE. The eigenvalues of the network mode  and the dynamic response of the series capacitor voltage after the fault can demonstrate the subsychronous frequency oscillation of the network (i.e. IGE). In the time domain simulations, the fault condition is the same as that in the study of TI. The compensation level of the series compensated transmission line initially is 74.2% as in the IEEE FBM.
6.1 Impact of compensation level
IGE is a purely electrical phenomenon, and it is largely dependent on the compensation level. As the compensation level changes, the influence of the wind farm on the IGE may also be different.
The simulation results indicate that the DFIG-based wind farm has a negative impact on the IGE at the compensation levels of 74.2% and 70%, while the positive influence will manifest as the compensation level decreases. So the impact of the DFIG-based wind farm on the IGE of the T-G unit depends on the compensation level of the series compensated transmission line.
6.2 Impact of wind farm scale
In this section, the impact of increased wind farm on the IGE of test benchmark will be investigated. In Case 2, there are 100 DFIG-based wind turbines in the wind farm at the beginning, and the output power of each wind turbine is 1.5 MW. Then, the number of wind turbines increases from 100 to 200, and the number of replaced generators in GEN 2 increases from 2 to 4 accordingly. During the above process, the control parameter Kp2 is fixed at 0.0025.
This paper has conducted a SSR analysis of the T-G unit when some conventional power plants were replaced by a DFIG-based wind farm. The influences of the wind farm on the TI and IGE of the T-G unit have been investigated. To evaluate the impacts, the IEEE FBM has been modified. Then, the eigenvalue analysis has been conducted based on the detailed mathematical model of the test benchmark. The results of the eigenvalue analysis have also been verified through the time domain simulations in the PSCAD/EMTDC.
The replacement of conventional power plants by the DFIG-based wind farm has a negative effect on the TI of the T-G unit, and it can be summarized as follows.
1) The larger the wind farm capacity, the less damping of the torsional oscillation.
2) The inner current controller of RSC have a significant impact on TI. The smaller proportional gain of the controller, the better damping of the torsional oscillation.
3) The higher the rotating speed of the DFIG, the less damping of the torsional oscillation.
On the other hand, the impact of replacement on the IGE depends on the compensation level. When the compensation level is high and the system is excited to lose its stability, the DFIG-based wind farm makes the oscillation even worse. When the compensation level is low enough to maintain the stability under the fault, the wind farm improves the damping of the oscillation. Meanwhile, the IGE will be worse if more conventional power plants are substituted by DFIG-based wind farms.
- Padiyar KR (2002) Power system dynamics: stability and control. BS Publications, DundasGoogle Scholar
- Kundur P (1994) Power system stability and control. McGraw-Hill, New YorkGoogle Scholar
- Anderson PM, Agrawal BL, Van Ness JE (1990) Subsynchronous resonance in power system. IEEE Press, New YorkGoogle Scholar
- Wilkes J, Moccia J (2013) Wind in power: 2012 European statistics. The European Wind Energy Association (EWEA), BrusselsGoogle Scholar
- IEEE Subsynchronous Resonance Task Force of the Dynamic System Performance Working Group, Power System Engineering Committee (1985) Terms, definition and symbols for subsynchronous oscillation. IEEE Trans Power Appar Syst 104(6):1326–1334Google Scholar
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