A Power System Stabilizer for DFIG-Based Wind ... - IEEE Xplore

IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 21, NO. 2, MAY 2006

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A Power System Stabilizer for DFIG-Based Wind Generation F. Michael Hughes, Olimpo Anaya-Lara, Member, IEEE, Nicholas Jenkins, Fellow, IEEE, and Goran Strbac, Member, IEEE

Abstract—A power system stabilizer (PSS) for a wind turbine employing a doubly fed induction generator (DFIG) is presented. It is shown that this PSS can significantly influence the contribution that a DFIG-based wind farm can make to network damping. A simple, generic test network that combines synchronous and wind farm generation is used to demonstrate system performance contributions. The results of both eigenvalue analysis and time response simulation studies are presented to illustrate contributions to network dynamic and transient performance that the DFIG controller with its PSS can make. Performance capabilities superior to those provided by synchronous generation with automatic voltage regulator and PSS control are demonstrated. Index Terms—Doubly fed induction generator (DFIG) control, dynamic stability, power system stabilizer (PSS), transient stability.

NOMENCLATURE Synchronous generator Terminal voltage vector. Field voltage, dc. Internally generated voltage vector (voltage behind transient reactance). Rotor flux vector. Rotor angle. Stator current vector. Synchronous reactance. Doubly fed induction generator (DGIG) Terminal voltage vector. Rotor voltage vector. Internally generated voltage vector (voltage behind transient reactance). Rotor flux vector. Angle between and axis of DFIG. Angle between and axis of DFIG. Stator frequency. Rotor speed. Slip, . Stator current vector.

Manuscript received August 18, 2005; revised November 18, 2005. This work was supported in part by EPSRC through its Supergen programme and in part by the Centre for Distributed Generation and Sustainable Energy sponsored by the Department of Trade and Industry (DTI), U.K. Paper no. TPWRS-00524-2005. F. M. Hughes is a consultant (e-mail: [email protected]). O. Anaya-Lara and N. Jenkins are with the Electrical Energy and Power Systems Group, University of Manchester, Manchester M60 1QD, U.K. (e-mail: [email protected]; [email protected]). G. Strbac is with the Electrical Energy and Power Systems Group, Imperial College London, London SW7 2AZ, U.K. (e-mail:[email protected]). Digital Object Identifier 10.1109/TPWRS.2006.873037

Rotor current vector. Transient reactance. Stator power output. Time response variables Stator power output of generator . P e Terminal voltage magnitude of generator . E mag Rotor angle of generator . Delta I. INTRODUCTION

T

HE increasingly widespread use of wind generation on power networks imposes the requirement that wind farms should be able to contribute to network support and operation, as do conventional generating stations based on synchronous generators. Early wind farms employed simple squirrel cage induction generators that operate at a speed that is substantially constant and as a consequence of this are normally referred to as fixed speed induction generators (FSIGs). Lacking control capability, such generation can contribute little to network support and relies on the network for the maintenance of adequate voltage levels for its successful operation [1]. While it can be shown that such FSIG-based wind farms can provide a contribution to network damping [2], their ability to survive network faults is poor. The use of a DFIG on a wind turbine not only improves the efficiency of energy transfer from the wind but also provides wind farms with the capability of contributing significantly to network support and operation with respect to voltage control, transient performance, and damping [1]. Recent grid codes have specified required contributions from DFIG-based wind farms with respect to voltage control and fault ride-through, but these requirements take scant advantage of the considerable control potential of DFIGs for network support. Excitation control of the synchronous generator of a conventional station can manipulate only the magnitude of the rotor flux vector, since the position of the rotor flux is dictated by the physical position of the rotor itself. In contrast, a DFIG has the capability of manipulating both the magnitude and the position of the rotor flux vector and as a consequence of this possesses a much greater control capability than does a synchronous generator. A DFIG is not only capable of providing a network with better voltage recovery and fault ride-through characteristics than can an equivalent size synchronous generator, but, as is shown in this paper, it can also considerably enhance network damping via an auxiliary power system stabilizer loop. Paradoxically, however, while in the U.K. new synchronous generators are required to

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have the capability of contributing to network damping and dynamic performance via the provision of a power system stabilizer (PSS), no such demand is made of DFIG-based wind farms. This paper demonstrates the control capabilities of DFIGbased wind farms and the significant enhancement to network damping that the addition of a PSS loop can provide. A simple generic network model, which has relevance to the U.K. power network for a projected wind generation scenario, is used for performance assessment purposes. Comparison is made of the situations where bulk generation provided by conventional synchronous generation is replaced by DFIG-based wind generation. It is shown that in situations where synchronous machinebased generation is close to the limits of stability, DFIG-based wind generation, even with a basic control scheme, provides better performance in terms of voltage control and damping. The major aims of this paper, however, are to demonstrate how the addition of a suitably designed PSS can enable a DFIGbased wind farm to considerably increase its contribution to network damping and that this can be achieved without degrading the quality of voltage control provided. This contrasts strongly with the case of PSS control on a synchronous generator where damping improvements are gained at the expense of reduced voltage control performance. II. MODELING OF A DFIG WIND TURBINE DFIG wind turbines use a wound rotor induction generator, where the rotor winding is fed through a back-to-back variable frequency PWM converter as shown in Fig. 1 [3], [4]. Voltage limits and an over-current “crowbar” circuit protect the machine and converters. For the studies of this paper, normal converter operation takes place for rotor current magnitudes less than twice the rated value. Otherwise, the crowbar protection acts to short circuit the rotor. The favored way of representing a DFIG for the purpose of analysis, simulation, and control is in terms of direct and quadrature axes ( axes), which form a reference frame that rotates synchronously with the stator flux vector [5]. In this paper, a frame is used to DFIG third-order model with respect to the represent the wind turbine [6]. This facilitates a good compromise between simplicity and accuracy. The assumption adopted that stator transients are sufficiently fast to be considered instantaneous makes the model compatible with the standard models used for synchronous generators and simplifies its integration into simulation models for transient and dynamic studies of mixed generation networks. III. PSS PROVISION A. Synchronous Generator Excitation Control A vector diagram representation of the operating conditions of a round rotor synchronous generator is shown in Fig. 2. In this diagram, represents the internally generated voltage in the stator, the magnitude of which is determined by the field , and hence the applied field voltage, . flux vector, The physical position of the field winding of the rotor with respect to the rotating stator voltage vector defines the position

Fig. 1. Schematic representation of a DFIG for a wind turbine application.

Fig. 2. Vector diagram representation of the operating conditions of a round rotor synchronous generator.

of the rotor flux vector and the -axis of the synchronously rotating reference frame. The internal generated voltage, , in per unit terms has the same magnitude as the field voltage, , and aligns with the -axis. For a given field voltage and terminal voltage, the rotor angle, , is determined by the output power of the generator. Generator control is exercised by adjustment of the magni, i.e., by the adjustment of the magtude of the field voltage, nitude of the internally generated stator voltage, . The automatic voltage regulator (AVR) loop of the excitation control system employs terminal voltage error for the adjustment of the , to control the terminal voltage magnitude. field voltage, Fast response excitation control enables tight control to be exercised over the terminal voltage but has the unfortunate side effect of reducing the damping torque of the generator at network oscillation frequencies [7]. Generator damping can be improved by introducing a PSS loop into the excitation control system [8]–[12]. However, this loop also has to exercise its control via the adjustment of the . In order to provide a damping contribution, field voltage, the field voltage needs to be adjusted in such a way that, under oscillatory system conditions, it induces a component of electrical power that is in phase with the oscillations in rotor speed. Since both AVR and PSS loops involve the adjustment of the , indesame variable, namely, the generator field voltage, pendent control over both terminal voltage and damping is not possible, and significant interaction exists between the PSS and AVR loops. Design involves a compromise between the conflicting requirements of voltage control and the provision of damping.

HUGHES et al.: PSS FOR DFIG-BASED WIND GENERATION

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Fig. 3. Vector diagram representation of the operating conditions of a DFIG.

B. DFIG Control Fig. 3 shows the equivalent vector diagram for a DFIG. In represents the internally generated voltage vector this case, in the stator (often referred to as the voltage behind transient depends on the magnitude of reactance). The magnitude of the rotor flux vector, . This flux is dependent on the generator stator and rotor currents but can be manipulated by adjustment of the rotor voltage vector, . The -axis of the defined synchronously rotating reference frame is chosen to align with the stator terminal voltage vector. The angle, , which defines the , with reposition of the internally generated voltage vector, spect to the stator voltage vector, (and hence the -axis of the reference frame), is determined by the power output of the , is generator. Since the internally generated voltage vector, orthogonal to the rotor flux vector, , the angle between the rotor flux vector, , and the -axis of the reference frame is also given by . A recent controller developed for DFIGs is the flux magnitude-angle controller (FMAC) scheme. The control philosophy adopted is to employ the adjustment of the magnitude of the , for the control of terminal voltage and rotor voltage vector, , for the control of electhe adjustment of its phase angle, trical power. Hence, in terms of the provision of AVR and PSS facilities for the DFIG, two independent control inputs are available, with the AVR loop employing the adjustment of the rotor , and the PSS employing the adjustment voltage magnitude, of the angle, . Following disturbances on the network, oscillations occur in the rotor speed and rotor angle of the synchronous generators supplying the power. These rotor angle oscillations give rise to oscillations in the currents of the generator field and damper circuits, and the energy dissipated in the resistance of these circuits provides the damping contribution of the synchronous generators to the power network. The currents generated due to the rotor oscillations produce a component of generator torque that is in phase with rotor speed and is normally referred to as the “damping” torque. With a DFIG, under oscillatory network conditions, the variations produced in the rotor and stator currents also give rise to energy dissipation in its windings, and while this does have a damping effect, due to the low resistance values involved, the contribution is quite small.

Fig. 4.

FMAC controller block diagram.

The presence of DFIGs on a network does, however, influence network damping [2]. The variations in the currents injected into the network by the DFIGs, in response to the network oscillations, produce variations in the load currents of the synchronous generators. These in turn lead to increased currents in their damper windings and consequently an increase in their damping torques. This ability to engender increased damping torques in the synchronous generators of the system can be further enhanced by appropriate control of the angle, , of the DFIG rotor flux, , or internally generated voltage, . The PSS needs to manipulate the angular position of the rotor flux vector with respect to the stator flux vector in such a way that the variations produced in the stator currents of the DFIG serve to increase the damping torques of the synchronous generators on the network. The PSS can employ as the control input any measured signal that is influenced by the network oscillations, such as DFIG rotor speed, slip, stator electrical power, or network frequency. IV. DFIG CONTROL SCHEME A. Basic FMAC Scheme The FMAC controller can take the control form presented in the block diagram of Fig. 4. The control scheme consists of two distinct loops. In the first loop, terminal voltage error is processed via the AVR to produce the reference value for the . magnitude of the control vector, , is In the second loop, the reference set point value, determined by the wind turbine power-speed characteristic for maximum power extraction for the prevailing wind velocity [3]. The power error is formed and processed to produce the reference value for the angular position of the control vector, , with respect to the stator voltage vector. The compensators of the AVR loop and the power loop are proportional plus integral controllers, with additional lead-lag compensation to provide suitable margins of loop stability in the AVR loop.

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Fig. 5.


Controller A block diagram.

Fig. 7.

Generic network model.

V. GENERIC TEST NETWORK

Fig. 6. PSS loop to enhance DFIG contribution to network damping.

The controller A of Fig. 4 employs the reference signals, and , to provide the rotor voltage vector, (in terms of and ) demanded from the converter, as shown in Fig. 5. PI control, with additional phase compensation to provide appropriate stability margins, is adopted in the individual loops. B. PSS Facility The PSS considered in this paper employs DFIG stator electrical power as its measured input signal. Stator electrical power is a readily available measurement and one widely used for the PSSs of synchronous generators. In the case of a DFIG, the phase compensation requirement of the PSS is much simpler when stator electrical power is used as the input signal compared with that when either slip or network frequency is employed. Consequently, stator electrical power was chosen as the most suitable PSS input signal. The PSS output signal may be applied at the internal summing or the external summing junction 2 junction 1 of Fig. 4. In the studies of this paper, summing junction 2 is chosen as this presents a PSS operating case that is more widely applicable to DFIG control in general. As summing junction 2 is external to the basic controller, the PSS signal, in principle, can be applied equally well to any DFIG controller [18], provided that the rotor voltage output demand of the controller is made available in polar, i.e., magnitude and phase angle form. The PSS loop takes the form shown in Fig. 6. The input signal is initially processed through a washout term (to eliminate any control contribution under steady conditions). The signal is then passed through a compensator that provides the necessary gain and phase shift to ensure appropriate control performance and a positive contribution to system damping. The parameters of the controller are provided in the Appendix.

The generic network model used in the studies is presented in Fig. 7. The network and data employed were arrived at in consultation with the major network operator on the U.K. system. It aims to provide a network model that, while simple in form, has relevance to a projected operating scenario with a large wind generation component sited in the Northern Scotland region. Generators 3 and 1 are steam turbine driven, round rotor synchronous generators provided with governor and excitation control. Generator 3 is chosen to be representative of the main England–Wales network and has a rating of 21 000 MVA. Generator 1 is chosen to be representative of the Southern Scotland network and has a rating of 2800 MVA. The generators are represented in terms of a standard sixth-order model. Both generators have a static excitation scheme with AVR control. The model and parameters of the excitation system are typical of those employed in simulation studies of the U.K. power network and are provided in the Appendix (see Figs. 17 and 18). For the DFIG control studies, Generator 2 is chosen to be representative of a projected wind generation situation on the Northern Scotland network and has a rating of 2400 MVA. The assumption is made that all of the wind generation is provided by DFIG-based wind farms having FMAC schemes with a PSS capability. Alternatively, the generation of the Northern Scotland network can be provided by conventional synchronous generation, having a rating equivalent to that of the rotating generation of the DFIG-based wind farm and the same control provision as modeled for generator 1. This situation is used to provide a base line case against which the contribution to network damping and performance of the DFIG controller and its PSS can be evaluated. The loads on buses 3 and 4 are modeled as constant impedances. However, reactive compensation is included on bus 4 to maintain the voltage profile of the network as the DFIG operating conditions vary. VI. PERFORMANCE ASSESSMENT METHODS The influence of PSS control on network damping can most readily be assessed by means of eigenvalue analysis [13]–[15]. For such analysis, disturbances are considered sufficiently small to permit the nonlinear model representing the power network


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TABLE I SLIP AND POWER OPERATING CONDITIONS CONSIDERED

to be linearized and expressed in state–space form. The eigenvalues of the linearized system, which define the fundamental modes of dynamic behavior, can then be calculated. For stability, all of the eigenvalues must lie in the left half complex plane. Any eigenvalue in the right half plane denotes an unstable dynamic mode and system instability. An indication of the damping contribution provided by a PSS is given by the shift to the left that it produces in the location of the eigenvalues associated with the dominant oscillatory modes. Control influence on large disturbance performance is assessed via time response simulation studies [16], [17]. A threephase fault is applied on one of the lines (X12b) connecting generator 1 to the central busbar, near to the terminals of the transand cleared 80 ms later former. The fault is applied at by opening switchgear A and B on the faulted line. With a DFIG, in order to maximize energy extraction from the wind, the operating slip is adjusted dependent on the prevailing wind speed. Consequently, DFIG performance is considered at both super-synchronous and sub-synchronous operating speeds, to . covering a range of slip values from The slip values considered and the respective power levels to which they correspond are listed in Table I. VII. SYNCHRONOUS GENERATOR WITH PSS CASE In this case, Generator 2, representing the Northern Scotland network, is considered to be a synchronous generator. The studies provide a base case against which the control contributions of the DFIG and its PSS control can be judged. A. Eigenvalue Analysis Fig. 8 shows how the locations of the dominant eigenvalues of the network vary as the gain of the PSS of synchronous generator 2 is increased from 0 to 5. The operating power level for MW. generator 2 is Since system response characteristics are comprised of an amalgam of the dynamic modes identified by the system eigenvalues, in general, it is not possible to directly link specific responses with individual eigenvalues. However, the two dominant oscillatory modes of the network shown in Fig. 8 can be associated with particular network oscillatory response characteristics and may be classified as follows: 1) mode 1 having a frequency of approximately 6 rad/s, corresponding to the situation where generator 1 oscillates against the main system; 2) mode 2 having a frequency in the range of 3.5 to 5 rad/s, corresponding to the situation where generators 1 and 2 oscillate in synchronism against the main system.

Fig. 8. Influence of PSS gain Kp2 of synchronous generator 2 on network dominant eigenvalues for operating power level, P = 1735 MW.

The loci shown in Fig. 8 indicate that without the PSS , the mode 2 eigenvalue pair has a positive real part, indicating negative damping and a dynamically unstable system. However, the introduction of the PSS on generator 2 can push the eigenvalue pair into the left half of the complex plane and make the network dynamically stable. , The loci of the eigenvalue pairs indicate that as the gain, of the PSS is increased, the damping associated with the lower frequency oscillatory mode 2 increases, while the damping of the higher frequency oscillatory mode 1 reduces. Time response studies indicate that under low damping conditions, the power oscillations induced in generator 2 lag those of generator 1. The difference in phase of the power oscillations of generators 1 and 2 serve to produce an oscillatory power component in generator 1 that is in phase with its rotor speed variations, and consequently, generator 2 contributes to the damping of generator 1. When the damping of generator 2 is increased due to PSS action, its power oscillations decay more quickly, and its damping contribution to generator 1 is consequently reduced. Hence, the damping associated with mode 1 is reduced by the PSS action on generator 2. B. Fault Studies The operating power level of MW, employed for the eigenvalue analysis, takes the system close to the transient stability limit for the fault considered. At power output values above the limit, both generators 1 and 2 lose synchronism with the main system following the fault. The responses shown in Fig. 9 employ a PSS gain of on generator 2. Although a higher gain value could provide a was chosen to higher level of damping, the value of reduce the impact that PSS limits exert on performance during the post fault period. Fig. 9 demonstrates that synchronism is retained and that the lower frequency mode (mode 2 of approximately 4 rad/s) is dominant. It can be seen that although PSS action provides damped performance following the fault, it leads

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Fig. 9. Synchronous generator case. Fault study transient responses of system = 2. generators. P = 1735 MW, = 80 ms, with PSS gain,

t

K

to considerable swings in the terminal voltage magnitude of generator 2. VIII. DFIG-BASED WIND FARM WITH PSS In these studies, generator 2 is assumed to be a DFIG-based wind farm controlled by the FMAC scheme having the PSS facility. A. Eigenvalue Analysis Fig. 10 indicates that when generator 2 is the DFIG, only one dominant oscillatory mode is in evidence. This mode has an oscillation frequency of approximately 6 rad/s. It therefore corresponds to the situation where generator 1 oscillates against the main system and is consequently equivalent to mode 1 of the purely synchronous generation case. The figure displays the location of the dominant eigenvalue pair for various values of slip over the permitted operating range. It can be seen that when generator 2 is the DFIG, even without the PSS, the system is stable. For the slip values considered, the eigenvalues cluster in a group having real parts mainly in to . This corresponds to damping factors of the range approximately 0.08 to 0.10. In Fig. 10, for each value of slip, the locations of the dominant eigenvalue pair are displayed for the cases where the DFIG control scheme operates both without and with the PSS loop. This enables the PSS damping contribution over the operating power range to be directly appreciated. When the PSS is introduced, the eigenvalues are shifted considerably to the left in the complex plane, indicating that a significant influence is exerted on the damping of the dominant , correoscillation of the network. At a slip value of sponding to the lowest operating power level of the DFIG, the real part of the dominant eigenvalue is increased to a value of ap. For higher values of DFIG speed (i.e., more proximately negative values of slip and higher levels of operating power), the PSS shifts the dominant eigenvalue further to the left of the complex plane. For a value of , corresponding to the highest operating power level, the real part has a value of

Fig. 10. Influence of PSS loop on the dominant eigenvalue over operating slip range. (With PSS ; without PSS ).

2

, corresponding to a damping factor of apapproximately proximately 0.28. The PSS exerts its influence by manipulating the stator current of the DFIG. Consequently, most influence is exerted when the stator current is greatest, i.e., when the stator power output is highest. It should be pointed out that for very small values of slip, i.e., for rotor speeds very close to the synchronous value, DFIG control is limited. The reason for this can be explained in terms of the way that the steady-state value of the rotor voltage vector, , is influenced by the operating slip value. (with reSteady-state values of the rotor voltage vector, spect to the axis reference frame of the DFIG), for various values of operating slip are displayed in Fig. 11. At high magnitude values of slip, the rotor voltage vector, , , have the apand the internally generated voltage vector, . Since the magnitude of proximate relationship, remains fairly constant over the operating range, the magnitude of the rotor voltage tends to be proportional to the magnitude of the slip. The relationship further indicates that at sub-synchronous speeds, where the slip is positive, the rotor voltage, , is approximately in phase with the internally generated voltage, , and at super-synchronous speeds, where the slip is negative, , is approximately in anti phase with . Fig. 11 shows that for low values of slip, the magnitude of the rotor voltage vector, , becomes small. Since DFIG control is exercised via the manipulation of , control capability is drastically reduced in the low slip region, making DFIG performance approach that of a squirrel cage induction generator ). In addition, it can be seen that over the slip (where to 0.03, the vector swings through an angle aprange proaching 180 . This indicates a drastically changing relationship between the rotor voltage vector, , and the internally gen, over the low slip region. erated voltage, Consequently, over the slip range covering the transitional region between sub and super synchronous operation, DFIG control is compromised by the varying dynamic characteristic and


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Fig. 13. DFIG case without and with PSS. s = line). b) DFIG without PSS (dashed line).

00 2. a) DFIG with PSS (full :

Fig. 11. Steady-state rotor voltage vector, v , for various values of s over the slip range.

Fig. 14. Comparison of DFIG and synchronous generator performance: a) DFIG with PSS, P 2e = 1735 MW, s = 0:137 (Full line). b) DFIG without PSS, P 2e = 1735 MW, s = 0:137 (Dashed line). c) Synchronous generator with PSS, P 2e = 1735 MW (Dotted line).

0

Fig. 12. Comparison of synchronous generator and DFIG influence on eigenvalue location due to PSS control.

nullified by the low magnitude of the rotor voltage that constitutes the control input variable. However, since a DFIG can operate at any value of slip over the design range, operation at low values of slip can be avoided. While the exclusion of a small range of operating speeds results in a slight reduction in the efficiency with which the turbine extracts energy from the wind over the range concerned, it has the benefit of ensuring that the significant control contributions that a DFIG can make to network support are sustained throughout its operation. Fig. 12 provides a direct comparison of the influence on damping that the respective PSS loops of the synchronous generator and the DFIG can provide. It can be seen that, in both cases, a considerable influence over the position of the dominant eigenvalue is achieved. However, since the basic

0

DFIG scheme without its PSS provides a level of damping on a par with that of the synchronous generator with its PSS, the contribution to network damping of the DFIG when its PSS is included is considerably greater than is possible in the synchronous generator case. B. Transient Performance Analysis Generator time responses in the super-synchronous range at values of slip of and , following the threephase short circuit of duration 80 ms, are presented in Figs. 13 and 15, respectively. The large disturbance simulation results confirm the damping contributions indicated by the eigenvalue analysis. Fig. 13 shows that the damping of the synchronous generators 1 and 3 are both substantially enhanced by the inclusion of the PSS on the DFIG. The dominant frequency oscillations are damped out within 4 s. With the PSS included in the DFIG control scheme, the performance is significantly better than that of the synchronous generator case of Fig. 9, both with respect to network damping and post fault voltage recovery.

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Fig. 15. DFIG case, without and with PSS. (Dashed line). b) With PSS (Full line).


s

=

Fig. 17. and 3).

Steam turbine and governor parameters (synchronous generators 1

Fig. 18.

Excitation control system (synchronous generators 1 and 3).

00 02: a) Without PSS :

Fig. 16. DFIG case, without and with PSS. s = 0:2: a) Without PSS (Dashed line). b) With PSS (Full line).

These characteristics are clearly shown in Fig. 14, where a direct comparison of DFIG and synchronous generator PSS control performance is provided. Fault study responses are superimposed for three cases, namely, synchronous generator with PSS control, DFIG without PSS control, and DFIG with PSS control. An initial operating power level for generator 2 of 1735 MW is considered in each case, which for the DFIG corresponds to an . Terminal voltage and stator operating slip level of power transients of generators 1 and 2 are presented. Fig. 14 not only demonstrates that the DFIG with its PSS provides much better damping than the synchronous generator with its PSS but also highlights the vastly superior voltage recovery that it provides for generator 2. The transient responses of Fig. 15 indicate that for an op, the PSS is still capable of erating slip value of enhancing network damping, even though the value of rotor voltage magnitude is relatively low. The rotor voltage vectors displayed in Fig. 11 indicate that despite the low rotor voltage , the rotor voltage vector still aligns magnitude at reasonably well with those corresponding to the slip values of

and . Consequently, the dynamic characteristic relating rotor voltage vector to the internally generated voltage is generally preserved, and the phase compensation provided in the PSS loop remains appropriate. Although the rotor , a good convoltage has lower magnitude than for tribution to system damping is still maintained through larger swings in the rotor voltage angle. This is reflected in the larger excursions seen in the stator power swings of generator 2 in ). Fig. 15 compared with those observed in Fig. 13 (for , Performance at the sub-synchronous slip value of corresponding to the lowest operating power level of the DFIG, is provided in Fig. 16. Again, despite the low power level, the PSS is seen to be capable of substantially improving network damping without sacrificing voltage control performance. IX. CONCLUSION A PSS has been presented that can significantly enhance the contribution that a DFIG-based wind farm can make to network


damping. The PSS of concern was designed for operation with a FMAC scheme for a DFIG that exercises control over terminal voltage and stator power output by the respective manipulation of the magnitude of the rotor flux vector and its angular position. In principle, however, the form of PSS control presented could be applied to other DFIG control schemes such as that of reference [18]. The proposed PSS has been shown to provide a DFIG-based wind farm with a consistently enhanced contribution to network damping over the full operating slip range envisaged for a DFIG. This range covers both the sub-synchronous and super-synchronous operating regions, apart from a small range of slip values close to zero, where the low magnitude of the rotor voltage involved and the variation in dynamic characteristics precludes an effective control contribution by a DFIG to network operation. It is shown that a wind farm with just the basic FMAC control scheme is capable of providing voltage control that is superior to, and a contribution to damping that is on a par with, that of conventional synchronous generation having both AVR and PSS control. The presented PSS controller is shown to provide a substantial, further increase in the DFIG contribution to network damping without degradation in the quality of voltage control. It consequently provides a much more effective and benign means of influencing network damping than the addition of PSS control on synchronous generation. By reducing the need for PSS control on synchronous generation for the provision of system damping, the introduction of PSS control on DFIG-based wind generation can benefit the quality of network voltage control. This paper demonstrates that FMAC control with the PSS provides DFIG-based wind generation with a much greater capability of contributing to network damping, dynamic performance, and transient stability than can be obtained from equivalent synchronous generation with conventional AVR and PSS control.

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Excitation control system (Generators 1 and 3)

DFIG parameters (on base of machine rating)

Converter power rating 25% of DFIG Nominal slip range Control parameters and transfer functions ; Voltage loop: Power loop:

;

;

;

APPENDIX Parameters of Generators 1 and 3 (p.u. on base of machine rating)

Generic network parameters (p.u. on base

)

prefault postfault

REFERENCES

Generator 1 , Generator 3 Steam turbine and governor parameters (Generators 1 and 3)

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F. Michael Hughes received the B.Eng. degree in electrical engineering with first class honors and the M.Eng. degree from the University of Liverpool, Liverpool U.K., in 1961 and 1963, respectively, and the Ph.D. degree in 1969 from the University of Manchester, Manchester, U.K. He was with Associated Electrical Industries Ltd. from 1961–1969 involved in the control of turbo generators and the dynamics of power systems. He was with the Nuclear Power Group Ltd. as a Senior Control Engineer, and in 1971, he joined the University of Manchester, where he was a Senior Lecturer until 1996. He is currently a consultant in power plant control and wind generation systems.

Olimpo Anaya-Lara (M’98) received the B.Eng. and M.Sc. degrees from Instituto Tecnológico de Morelia, Morelia, México, and the Ph.D. degree from University of Glasgow, Glasgow, U.K., in 1990, 1998 and 2003, respectively. His industrial experience includes periods with Nissan Mexicana, Toluca, Mexico, and CSG Consultants, Coatzacoalcos, México. Currently, he is a Research Associate with the Electrical Energy and Power Systems Group at the University of Manchester, Manchester, U.K. His research interests include wind generation, power electronics, and stability of mixed generation power systems.

Nicholas Jenkins (SM’97–F’05) received the B.Sc. degree from Southampton University, Southampton, U.K., the M.Sc. degree from Reading University, Reading, U.K., and the Ph.D. degree from Imperial College London, London, U.K., in 1974, 1975, and 1986, respectively. His industrial experience includes periods with Eastern Electricity, Ipswich, U.K., Ewbank Preece Consulting Engineering, Brighton, U.K., and BP Solar and Wind Energy Group, London, U.K. He joined the University of Manchester, Manchester, U.K., in 1992, where he is now a Professor and Leader of the Electrical Energy and Power Systems Group. His research interests include renewable energy, embedded generation, and FACTS.

Goran Strbac (M’95) is a Professor of electrical energy and power systems at Imperial College London, London, U.K. He has led a number of national and international research and consultancy projects on technical and economic aspects of system integration of distributed and renewable generation. His work also includes development and optimization of transmission and distribution system investment strategies and pricing of network and ancillary services.