Overview of Control Systems for the Operation of DFIGs in Wind ...

2776 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 60, NO. 7, JULY 2013

Overview of Control Systems for the Operationof DFIGs in Wind Energy Applications

Roberto Cárdenas, Senior Member, IEEE, Rubén Peña, Member, IEEE,Salvador Alepuz, Senior Member, IEEE, and Greg Asher, Fellow, IEEE

Abstract—Doubly fed induction generators (DFIGs), often or-ganized in wind parks, are the most important generators usedfor variable-speed wind energy generation. This paper reviews thecontrol systems for the operation of DFIGs and brushless DFIGsin wind energy applications. Control systems for stand-aloneoperation, connection to balanced or unbalanced grids, sensor-less control, and frequency support from DFIGs and low-voltageride-through issues are discussed.

Index Terms—Control strategies, crowbar, doubly fed inductiongenerator (DFIG), low-voltage ride through (LVRT), reactive sup-port, robust controller, voltage unbalance, wind turbine.

NOMENCLATURE

ims Magnetizing current vector.is Stator current vector.ir Rotor current vector.if Grid-side converter (GSC) current vector.J Rotor inertiaktransf Constant for the abc-to-d–q transformation.Ls Stator inductance.Lr Rotor inductance.L0 Magnetizing inductance.ωe Synchronous angular frequency.ωr Rotational angular frequency.ωsl Slip frequency.p Number of poles.ψs

Stator-flux vector.ψr

Rotor flux vector.Rs Stator resistance.Rr Rotor resistance.s Slip.Te Electrical torque.vs Stator voltage vector.

Manuscript received June 19, 2012; revised October 5, 2012; acceptedDecember 20, 2012. Date of publication January 30, 2013; date of currentversion February 28, 2013. This work was supported in part by the FondoNacional de Ciencia y Tecnología, Chile, under Contract 1110984 and Contract1121104 and in part by the Industrial Electronics and Mechatronics MillenniumNucleus.

R. Cárdenas is with the Department of Electrical Engineering, University ofChile, Santiago 837-0451, Chile (e-mail: [email protected]).

R. Peña is with the Department of Electrical Engineering, University ofConcepción, Concepción 407-4580, Chile (e-mail: [email protected]).

S. Alepuz is with the Mataró School of Technology, Polytechnic Universityof Barcelona, 08302 Mataró, Spain (e-mail: [email protected]).

G. Asher is with the Department of Electrical and Electronic Engineering,University of Nottingham, Nottingham, NG7 2RD, U.K. (e-mail: [email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TIE.2013.2243372

v1s Positive sequence of the stator voltage.v2s Negative sequence of the stator voltage.v0 Zero sequence of the stator voltage.vr Rotor voltage vector.vf GSC voltage vector.θsl Slip angle.θs Position of the stator-flux vector.θr Rotor position.τs Stator time constant.

I. INTRODUCTION

THE DOUBLY fed induction machine (DFIM), also knownas the wound-rotor or slip-ring induction machine, is an

induction machine with both stator and rotor windings [1], [2].The DFIM is nowadays widely used as a generator, particularlyin variable-speed wind energy applications with a static con-verter connected between the stator and rotor. Currently, thistopology occupies close to 50% of the wind energy market [3].Table I shows some of the commercially available wind energyconversion systems (WECSs), with power in the range of1.5–3 MW, which are based on doubly fed induction generators(DFIGs). In total, in Table I, there are 93 models of WECSsbased on DFIGs for that power range. In Table I, “NM” standsfor number of models.

DFIGs are also used in higher power ranges (> 3 MW).The German company Repower manufactures two models ofWECSs based on DFIGs, the model 6M with a total outputpower of 6150 kW and the model 5M with a total output powerof 5 MW [4].

For WECSs based on DFIGs, gearboxes are required becausea multipole low-speed DFIG is not technically feasible [5]. Thedesign of a DFIG-based WECS with a one-stage gearbox wasproposed in [6], but no commercial WECS has been imple-mented with this concept. However, even with the problemsassociated with a three stage (3S) gearbox, the DFIG still hassome advantages when compared with other generators used inwind energy applications [3]. For instance, in [7] and [8], threegenerators suitable for wind energy applications are studied:a direct-drive synchronous generator (SG) (which is one ofthe solution offered by Enercon [9]), a direct-drive permanent-magnet generator (PMG) [10]–[14] (marketed by several com-panies, e.g., Vestas [13], Clipper [14], and Dewind), and a3S-geared DFIG (see Table I). The results in terms of weight,cost, size, and losses obtained in [7] and [8] are presented inTable II. Notice that the 3S-Geared DFIG is considered the basefor the comparison.

0278-0046/$31.00 © 2013 IEEE

CÁRDENAS et al.: CONTROL SYSTEMS FOR OPERATION OF DFIGs IN WIND ENERGY APPLICATIONS 2777

TABLE ICOMMERCIALLY AVAILABLE WECSs IN THE

RANGE OF 1.5–3 MW BASED ON DFIGs

TABLE IICOMPARISON BETWEEN THREE GENERATORS PUBLISHED IN [7] AND [8]

From Table II, it is concluded that the total weight of a WECSbased on a direct-drive PMG is about 4.5 times higher than thatof a WECS based on a DFIG [7], [8]. The stator diameter of adirect-drive PMG is about six times that of a DFIG of similarpower. Recently, the performance of the DFIG has been alsocompared with that of the medium-speed permanent-magnetSG (PMSG) in [8]. The medium-speed PMSG, usually coupledto a single-stage gearbox, is a relatively new topology forvariable-speed wind generation (also known as the “Multibrid”concept [3]) and has been adopted by some WECS manufactur-ers, e.g., Vestas, Areva, and WinWinD [3].

One of the main reason for the popularity of DFIGs in windenergy applications is that relatively small power convertersare required to control the generator. For a typical DFIG, thepower converters are connected in the rotor circuit and, forrestricted speed range, are rated at a fraction (usually 30%) ofthe machine nominal power [15]–[17]. Typically slip rings arerequired in order to connect the machine-side converter to therotor. Brushless topologies are also feasible [18]–[22].

Because of the popularity of DFIGs for wind energy gener-ation, control systems suitable for this application have beenextensively investigated. Control methods for grid-connectedWECSs, stand-alone systems, frequency support using DFIGs,low-voltage ride-through (LVRT) control, etc., have been pre-sented and discussed in the literature. The aim of this paper is togive an update of the most recent trends regarding DFIG controlsystems. In this respect, it augments previous overview papers[23], [24]. In particular, this paper highlights the most recentissues in sensorless control of DFIGs, droop control, the appli-cation of DFIGs to microgrids, and the latest work in LVRT.

This paper is organized as follows. In Section II, speed andtorque control of DFIGs is discussed, and the maximum powerpoint tracking (MPPT) control of DFIGs is also analyzed. InSection III, control of DFIGs connected to unbalanced gridsis presented. Section IV addresses DFIG sensorless controlmethods, whereas Section V discusses frequency support usingDFIGs. LVRT control is discussed in Section VI. Finally, theconclusions are presented at the end of this paper.

II. SPEED AND TORQUE CONTROL OF DFIM

A. OptiSlip of Vestas

In the past, external resistors were connected to the slip ringsof wound-rotor machines in order to reduce the starting current(for motor operation) or for maximizing the electrical torque ina given operating point. The use of external resistors, at least forthese applications, is now considered obsolete because betterperformance is obtained using power electronics as soft starters,pulsewidth-modulated (PWM) inverters, etc. However, externalresistors connected to the rotor are still used in some topologiesof WECSs based on wound-rotor induction machines.

Vestas in its OptiSlip scheme [25]–[27] (e.g., Vestas V39–600, V66–1.65 MW) places the resistors and electronic com-ponents (as current sensors, insulated-gate bipolar transistors(IGBTs), and part of the control hardware) mounted in the rotor,i.e., no slip rings are required. Depending on the operating pointof the WECS, different ohmic values of resistors are connectedto the rotor windings using the IGBT transistors. The signals forthe control of the IGBTs are transmitted via an optical link fromoutside the rotor. This topology is designed for a slip variationof up to 10%, delivering a smoother power to the grid [25],[26], [28]. Moreover, the mechanical stresses on some parts ofthe wind turbines are drastically reduced [25].

A further development of the OptiSlip is the OptiSpeedscheme, which allows slip variations of about 60% [28]. Theuse of external resistors connected to the rotor could be aug-mented with pitch control in order to improve the performanceof the WECS in dynamic operation, e.g., in the presence of agrid disturbance [27].


Fig. 1. Static Scherbius scheme with two back-to-back PWM VSIs.

Even when the OptiSlip of Vestas has an important shareof the total WECSs installed in the world (≈11% in 2008according to [27]), the main disadvantage of this topology is inits relatively low efficiency because of the dissipation of energyin the external resistors.

B. Static Scherbius Drive

The Scherbius system was proposed by the German engineerArthur Scherbius in the early years of the 20th century. Thescheme allows bidirectional power flow in the rotor circuit sothat operation of the machine below and above synchronousspeed is possible. Several topologies have been used in thisscheme [1], [2], [15], [17], [29]–[51]. The first work reportedin the literature uses a topology similar to the static Kramerdrive discussed in [52], but with the rotor diode bridge replacedby a current-fed (naturally commutated) dc-link converter [32],[44], [46], [53]. Another early topology of the Scherbius driveuses a cycloconverter connected between the stator and therotor [43], [50], [54], However, the current-fed converters andthe cycloconverters produce high harmonic content in the rotorcurrent, which are reflected in the stator due to the transformeraction of the machine.

The disadvantages of the naturally commutated converterscan be overcome by the use of two PWM voltage-fed current-regulated inverters connected back to back in the rotor circuit[15], [17], [29]–[31], [33], [35]–[42], [45], [47]–[49], [51],[55]. The scheme is shown in Fig. 1. This topology allows:

• bidirectional power flow with operation below and abovesynchronous speed with the speed range restricted only bythe rotor voltage rating of the DFIG;

• operation at synchronous speed with dc injected into therotor, with the rotor-side inverter operating in choppingmode;

• low distortion stator, rotor, and supply currents;• independent control of the torque and rotor excitation;• control of the displacement factor between the voltage and

the current in the GSC and, hence, control over the systempower factor.

The application of direct frequency power converters, namelymatrix converters (MCs), and indirect MCs (IMCs) has beenproposed as an alternative to the back-to-back voltage sourceinverter (VSI) topology shown in Fig. 1 [56], [57]. Thesetopologies are all-silicon solutions for ac–ac conversion withsinusoidal input and output currents without using passivecomponents in the dc link. However, the lack of energy storage

devices in the MCs could be a problem to obtain a goodperformance for LVRT conditions. Further investigation aboutthis issue is required before considering the MCs as suitablecandidates for controllings DFIGs in WECSs.

C. Vector Control of DFIMs

The vector control technique developed for squirrel-cageinduction machines [1], [58] can be extended to DFIMs [15].Usually, in a cage induction machine fed by an inverter con-nected to the stator, the stator currents are controlled using ad–q rotating frame aligned with the rotor flux. By analogy,in DFIMs, the rotor is fed by an inverter; therefore, the rotorcurrents are usually controlled using a rotating frame alignedwith the stator flux [15], [16]. Under this scheme, the electricaltorque is proportional to the q-axis rotor current. Because thestator is connected to the utility in grid-connected applications,the d-axis rotor current can be used to regulate the reactivepower flow in the machine. In wind energy applications, MPPTis usually carried out by controlling the machine electricaltorque [15], [41], [55]. This is discussed in Section II-G.

The machine equations for a DFIG in a d–q synchronousframe orientated along the stator flux are as follows [1], [15]:

⎡⎢⎣ψds

ψqs

ψdr

ψqr

⎤⎥⎦ =

⎡⎢⎣Ls 0 L0 00 Ls 0 L0

L0 0 Lr 00 L0 0 Lr

⎤⎥⎦⎡⎢⎣idsiqsidriqr

⎤⎥⎦ (1)

[vdsvqs

]=

[Rs 00 Rs

] [idsiqs

]+

d

dt

[ψds

ψqs

]

+

[0 −ωe

ωe 0

] [ψds

ψqs

](2)

[vdrvqr

]=

[Rr 00 Rr

] [idriqr

]+

d

dt

[ψdr

ψqr

]

+

[0 −ωsl

ωsl 0

] [ψdr

ψqr

](3)

Te = ktransfp

2L0(iqsidr − idsiqr) (4)

where subscripts d and q denote direct and quadrature compo-nents referred to the synchronous rotating frame, respectively;and subscripts r and s denote stator or rotor quantities, respec-tively. ψ

s= L0 · ims is the stator flux, where ims is known as

the magnetizing current.The field orientation for machine variable transformation

uses slip angle θsl derived from the position of the stator-flux vector θs and the rotor position θr (see [15] and [16]) asfollows:

θsl = θs − θr. (5)

The position of the stator-flux vector θs can be obtained fromthe stator-flux α–β components as

θs = tan−1

(ψβs

ψαs

). (6)


Fig. 2. Control schematic of a DFIG.

An alternative to (6) is to use a phase-locked loop (PLL) [59]to obtain θs. The α–β components of the stator flux can becalculated from the stator voltages and currents as

ψαs =

∫(vαs −Rsiαs) dt

ψβs =

∫(vβs −Rsiβs) dt. (7)

The expression in (7) requires an integrator. However, inpractical implementations, a pure integrator can be replaced bya low-pass filter or a bandpass filter (BPF) used as a modifiedintegrator to block the dc component of the measured voltagesand currents [60], [61]. The BPF is typically designed with acutoff frequency of 0.1 to 1 Hz. Because the stator voltagesand currents are 50-Hz signals, the performance deteriorationfrom integral action is negligible [61]. The control schematicis shown in Fig. 2, where E is the converter dc-link voltage,and the superscript “∗” denotes a demand value. When theorientation along the stator flux is correct, the electrical torqueis given by

Te = ktransfp

2

L20

LsimsIqr = kt1imsiqr (8)

with the torque constant kt1 = ktransfpL20/Ls. The stator mag-

netizing current ims = ψds/L0 is practically constant in grid-connected applications. Under flux orientation conditions, themagnetizing current can be provided: 1) entirely from the statorwith ird = 0; 2) entirely from the rotor with isd = 0; or 3) acombination of magnetizing currents supplied from both thestator and the rotor. This degree of freedom regarding thereactive power flow in the machine can lead to an optimizationproblem, where losses in the machine and ratings of the rotor-side and the line-side converters need to be considered [41],[62]. The electrical torque is proportional to irq , and the reactivepower in the machine can be regulated by acting upon ird.

Vector control schemes can also be implemented using areference frame oriented along the stator voltage vector andcontrolling the stator currents instead of the rotor currents. The

Fig. 3. Voltage vectors and stator and rotor fluxes.

dynamic performance of the controlled currents is similar, butin this case, the d-axis and q-axis stator current componentsare proportional to the stator active and reactive power [30].Standard modulation techniques could be used to provide thePWM patterns to the rotor-side converter (RSC)/GSC [63]–[65]. For parallel connection of power converters, shifting ofthe PWM patterns could be implemented in order to reduce thetotal harmonic distortion [64].

D. DTC of DFIM

The direct torque control (DTC) technique [66], widelyapplied to squirrel-cage induction machines, has also been usedto control the electrical torque in the DFIM because of the gooddynamic performance that it achieved [31], [39], [40], [45],[67]–[69]. ABB has developed a low-voltage power converterto control a DFIM for wind power applications using thistechnique [70].

A two-level voltage-fed inverter can impose six active vec-tors and two zero vectors at the machine rotor terminals, asshown in Fig. 3(a). These voltage vectors, when applied fortime interval Δt, produce changes in the rotor flux vector bothin magnitude and phase with respect to the stator-flux vector(see also Fig. 3). It can be shown that the electrical torque isproportional to the cross product of the stator and rotor fluxvectors, i.e.,

Te = ktψs ⊗ ψr = kt|ψs||ψr| sin δ (9)

where kt is a constant dependent on the machine parameters.Assuming grid-connected operation, the stator-flux magni-

tude is practically constant. Therefore, the rotor flux vectorcan be changed by applying different rotor voltages via theRSC. From (9), this produces changes in the electrical torque(and generated reactive power). Depending on the position ofthe rotor and for a desired change in the electrical torque androtor flux magnitude, there is an optimum voltage vector to beapplied to the machine [2], [45].

In order to implement the DTC strategy, it is necessary toknow the rotor flux vector in magnitude and angle, and theelectrical torque. The rotor flux can be obtained using (1) withthe stator and rotor currents referred to the α–β reference frameaffixed to the rotor, i.e.,

|ψr| =√

ψ2αr + ψ2

βr

ψ2r =L0i

rαs + Lriαr; ψβr = L0i

rβs + Lriβr

∠ψr = tan−1(ψβr/ψαr) (10)


Fig. 4. DTC for DFIM.

where irαs and irβs are the α–β components of the statorcurrent referred to the rotor frame. The electrical torque can beobtained as

Te = kt2(ψαriβr − ψβriαr) (11)

where kt2 is dependent on the α–β transformation being used.The control diagram of a standard DTC strategy is shownin Fig. 4.

E. DPC Applied to DFIMs

The direct power control (DPC) technique was proposedabout 15 years ago for controlling three-phase PWM rectifiers[71]–[73]. It follows the same philosophy of DTC, but it alsolooks at the effect of the stator and rotor fluxes upon the statoractive and reactive power. It can be shown that stator activepower is proportional to the rotor flux component perpendicularto the stator flux where the stator reactive power is proportionalto the rotor flux component aligned with the stator flux [44].

The approach can be extended to DFIMs [29], [42], [45],[49], [51], [74]. A DPC strategy minimizing the use of zerovoltage vectors is presented in [49]. When using DTC at lowrotational speed, zero voltage vectors are more frequently ap-plied to the machine terminals causing a flux reduction becauseof the stator resistance. In DFIMs, the equivalent situation is theoperation near or at synchronous speed where the rotor voltageapplied to the machine is low. Operation at or near synchronousspeed is not uncommon when the machine is used in variable-speed WECSs.

The operation principle is to control directly the stator activeand reactive power by applying the proper voltage vector in themachine rotor. The stator power can be calculated as

Pe = ktransf(vαsiαs + vβsiβs)Qe = ktransf(−vαsiβs + vβsiαs). (12)

The error between the reference active and reactive powerand the calculated active and reactive power in the machineare processed by hysteresis controllers. Schemes employingboth two-level and three-level hysteresis controllers have beenreported in the literature [45], [49]. The implementation of thestrategy needs the α–β rotor flux vector position within six pre-defined sectors in the rotor coordinates in order to determine theoptimal rotor voltage vector to apply to the machine. Becausethe rotor flux vector position needs to be known, the standard

Fig. 5. DPC scheme as reported in [49].

DPC approach requires, as the standard DTC strategy, statorand rotor current measurements. However, it is claimed in [71]–[73] that DPC is less dependent of the machine parameters.

In order to reduce the strategy parameter dependence, alter-native schemes have been used. A strategy based on the stator-flux position, which is referred to the rotor, and the effect ofthe different voltage vectors upon the stator active and reactivepower is presented in [44]; therefore only stator voltage andcurrents are measured. A schematic of this strategy reported in[49] is shown in Fig. 5.

Another strategy to estimate the rotor flux position is pre-sented in [40], where an adaptive mechanism based on the effectof voltage vectors upon the reactive power variation is pre-sented. However, the strategy requires a rather high samplingfrequency. Again, only the stator current and voltages need tobe measured in order to implement the DPC.

The control schemes presented in Section II-D–F have beenvery well documented in the literature. The strategies pro-vide good overall performance, but it is not straightforwardto establish the superiority of one over the others. A faircomparison would have to include dynamic-state and steady-state performances, current ripple content, and losses in theconverters. The vector control approach is based on the machinemodel and is more parameter dependent: the implementationcomplexity might be higher; currents, voltages, and positionneed to be measured (although implementation without encoderis feasible); and the current control dynamics are reasonablewith no high sampling frequency. On the other hand, DTCimplementation is simpler, even if it is a model-based approach,and is less dependent on machine parameters: high torquedynamics can be achieved, but higher nonconstant switchingfrequencies are typical; a higher current ripple is expected,higher bandwidth of current and voltage sensors are neededand rotor position needs also to be measured. Finally, DPCcould be even simpler to implement: good power dynamics canbe achieved with high variable switching frequency; a highercurrent ripple is usual and higher bandwidth of current andvoltage sensors are also needed, but rotor position does not needto be measured.

If MPPT is considered, speed measurement/estimation istypically required for any of the control strategies discussedearlier. The MPPT implementation is straightforward for DTCand vector control approaches because the electrical torque


Fig. 6. Locus for the maximum aerodynamic efficiency, in the power-speedplane, for a typical variable-speed wind turbine.

is directly or indirectly controlled. However, DPC controlsonly the stator power, and MPPT requires regulation of thetotal power supplied to the grid or isolated load. Therefore,the rotor power has to be considered, and this increases theimplementation complexity of the MPPT algorithm.

F. Control of the GSC

The objective of the line-side converter or the GSC in thetopology depicted in Fig. 1 is to permit the active power flow,regulating the dc-link voltage to a constant level. Close-to-unity power factor operation is usual, but it is also possible tocontrol the reactive power flow between the converter and thestator/grid. A vector control approach is normally used [15],[55], with a reference frame oriented along the grid-voltagevector, enabling independent control of the active and reactivepower flowing between the grid and the GSC. The grid-sidePWM converter is current regulated, with the d-axis currentregulating the dc-link voltage and the q-axis current regulatingthe reactive power. Alternatively, DPC can be also applied to thecontrol of the GSC, leading also to a decoupled control of theactive and reactive power flows in the converter [29], [71]–[73].

G. MPPT Control

For a typical variable-speed wind turbine, the locus of themaximum aerodynamic efficiency corresponds to a cubic linerelating the power captured with the rotational speed [75]–[81].This is shown in Fig. 6. The optimal power Popt is related tothe rotational speed of the blades by the following nonlinearfunction:

Popt = koptω3r (13)

where kopt is a function of the parameters of the WECS, e.g.,gearbox size, blade radius, blade profile, etc. Two types ofMPPT algorithms have been reported in the literature, i.e., thespeed control and torque control of the electrical generator formaximum aerodynamic efficiency [82], [83]. For the MPPTalgorithms based on speed control, the generator rotationalspeed is regulated to drive the WECS to the point of maximumaerodynamic efficiency. Further discussion of MPPT methodsbased on speed control is considered outside the scope of thispaper and the interested reader is referred elsewhere [82], [83].

Fig. 7. Some simple control system for MPPT in DFIG-based WECSs.(a) Control system of (13) and (14), as discussed in [77] and [78]. (b) Controlsystem of (15), as discussed in [55] and [84].

For the MPPT algorithms based on torque control, thequadrature current i∗qr is regulated to drive the WECS to thepoint of optimal power capture. As discussed in [77] and [78]to drive the WECS to the point of maximum aerodynamicefficiency, the electrical torque could be controlled as

T ∗e = koptω

2r . (14)

Using (8) and (14), the quadrature reference current i∗qr canbe calculated as

i∗qr =koptkt1ims

ω2r . (15)

If the machine parameters are correctly identified, the simplecontrol strategy of (15) can be used to drive the WECS to thepoint of maximum aerodynamic efficiency.

The control system based on (15) is shown in Fig. 7(a). Therotational speed of the generator is used as the input of a lookuptable (or nonlinear function), where (15) is stored. Current i∗qr isobtained at the lookup table output and is used as the referenceof the quadrature current control loop.

Another alternative is to implement optimal power trackingusing an additional control loop. This strategy has been reportedin [55] and [84]. The control system calculates the powerreference P ∗

e using a lookup table, where the optimal power asa function of the rotational speed is stored [see Fig. 7(b)]. FromP ∗e , the rotor torque current is calculated as

i∗qr = Kp(P∗e − Pe) + ki

∫(P ∗

e − Pe) dt (16)

where kp and ki are the proportional and integral constantsof the proportional–integral (PI) controller. Pe is the electricalpower supplied by the DFIG to the grid, which is measured bythe voltage and current transducers. The control system shownin Fig. 7(b) requires nested control loops with the bandwidth ofthe outer loop being a fraction of the internal current iqr loop.


Fig. 8. DFIG feeding a stand-alone load.

The main advantage of the control strategy of (16) [andFig. 7(b)] is that the errors in the machine parameter estimation,e.g., kt1 and ims in (15), are compensated by the PI controller.On the other hand, the relationship between the torque rotorcurrent and power Pe is dependent on the rotational speed,and some compensation strategy, for instance gain schedulingcontrol, could be required to maintain a good dynamic responsein the whole operating range.

Here, only two simple control strategies have been ex-plained. However, other power tracking methodologies (as thespeed-control-based MPPT algorithms discussed in [77] and[85]–[87]) e.g., perturbation and observation, wind speed ob-servers, etc., can be applied to WECSs based on DFIGs.

III. CONTROL SYSTEMS FOR THE CONNECTION

OF DFIGS TO UNBALANCED SYSTEMS

A WECS may be installed in remote rural areas, where weakgrids with unbalanced voltages are not uncommon [42], [88]–[90]. Moreover, in stand-alone applications, the DFIGs can feedunbalanced and islanded loads [91]–[95].

As reported in [89], [90], and [96]–[99], induction machinesare particularly sensitive to unbalanced operation since lo-calized heating can occur in the stator, and the lifetime ofthe machine can be severely affected. Furthermore, negative-sequence currents in the machine produce pulsations in theelectrical torque, increasing the acoustic noise and reducing thelife span of the gearbox, blade assembly, and other componentsof a typical WECS [88], [91], [92], [100].

For the control of DFIGs operating in unbalanced systems,control algorithms based on counterrotating synchronous d–qaxes [89], [91], [92], [98], [101], resonant control [95], [102],[103], predictive control [93], [104], [105], sliding control[106], and DPC [29], [42] have been proposed in the literature.

A. Control of a DFIG Feeding a Stand-AloneUnbalanced Load

Fig. 8 shows a DFIG feeding a stand-alone load. TheDFIG stator and the load are star-connected with the neutralpoints connected, to provide a path for the circulation of zero-sequence currents. A four-leg grid-side inverter can be alsoused to supply zero-sequence signals to a star-connected linear/nonlinear unbalanced load [107]–[109].

The initial excitation for the system start up could be pro-vided by a battery bank (not shown in the figure). The batterycould be kept charged afterward using the energy flow inthe dc link. Another possibility is to use a bank capacitor inthe stator for the self-excitation of the machine, generating the

Fig. 9. Control system discussed in [91].

required stator voltage. Then, the control strategy of the line-side converter or, in this case, the stator-side converter, couldregulate the required dc-link voltage.

To compensate the load unbalance, the GSC and/or the RSCcan be used. For instance, in [91] and [92], the use of the GSCto compensate the load unbalance is proposed. The controlsystem discussed in [91] is shown in Fig. 9. (Only the GSCcontrol system is shown.) The positive-sequence vector controlsystem is oriented along the stator voltage vector. Because ofthe unbalance, a PLL is implemented to calculate the statorvoltage angle θv [59]. From +θv and −θv, the currents canbe referred to two synchronous d-axis and q-axis rotating at+ωe and −ωe, respectively. Doubly frequency componentsare produced when the positive/negative-sequence currents arereferred to the d-axis and the q-axis rotating in the oppositedirection. As shown in Fig. 9, notch filters are used to eliminatethese high-frequency components [89], [91], [92], [98], [101].The output of theses filters are the currents i+df , i+qf , i−df , and i−qf .

The control systems for the front-end positive-sequence cur-rents i+df and i+qf are entirely conventional (see Fig. 9, and

[91] and [92]). Current i+df regulates the dc-link voltage E, and

current i+qf regulates the reactive power supplied to the load.The front-end negative-sequence currents are regulated to

i−∗dqf = −i−dqL = −

(i−dqs + i−dqf

). (17)

Therefore, the negative-sequence current demand is a functionof the load negative-sequence current. In the steady state, wheni−dqf = −i−dqL, stator current i−dqs = 0 [see (17)], and the torquepulsations are eliminated.


Fig. 10. Experimental results corresponding to the control system discussedin Fig. 9. (a) Negative-sequence currents. (b) Stator and rotor unfiltered currentsreferred to the d–q positive-sequence axes.

In abc coordinates, the total voltage demand for the front-endconverter is obtained as (see Fig. 9)

vabc = v+abc + v−abc. (18)

Fig. 10 shows the performance of the control system de-picted in Fig. 9 for negative-sequence current compensationunder variable-speed stand-alone operation (see [92]). The loadconsists of three unbalanced resistors connected to phases a,b, and c, respectively (see Fig. 8). The rotational speed isvaried from ≈1350 to ≈1650 rpm to illustrate the performanceat variable speed (from below to above synchronous speed).Before t ≈ 1.25 s, the compensation system is not operating,and the stator current has a negative-sequence component [seeFig. 10(a)]. In t ≈ 1.25 s, the compensation is enabled, and thestator current i−dqs is driven to zero. For t > 1.5 s, i−dqL ≈ i−dqf ,and the negative-sequence currents are eliminated from themachine stator. Notice that the term “unfiltered” indicates thatthe displayed currents have not been filtered by the notch filtersshown in Fig. 9.

There are other publications where control of a stand-aloneunbalanced load is discussed. For instance, the control systemdiscussed in [94] uses the RSC to regulate a balanced loadvoltage. In this study, the control system is tested with nonlinearloads and the authors claim a good performance. However, themain disadvantage of [94] is that the rotor current reference hasnegative-sequence components, and a relatively large dc-linkvoltage could be required to regulate these components.

Predictive control systems for DFIGs feeding unbalancedstand-alone loads are discussed in [93] and [105]. In this case,the voltage vector that minimizes a cost function is identifiedand applied to the RSC. The control discussed in [93] and [105]use only the RSC to compensate the unbalances in the stand-alone load.

To the best of our knowledge, the only publication reportingthe use of both the RSC and GSC to compensate the loadunbalance in a stand-alone DFIG is [95]. In this case, a d–q con-trol system augmented with a resonant controller (implementedin the synchronous rotating frame) is proposed. The RSC iscontrolled to regulate a balanced load voltage, whereas the GSC

Fig. 11. DFIG feeding an unbalanced grid.

is controlled to eliminate the negative-sequence currents fromthe stator of the DFIG.

B. Control of a DFIG Feeding an Unbalanced Grid

Fig. 11 shows a DFIG feeding an unbalanced grid. In thiscase, the aim of the control system is no longer to regulatethe grid voltage. The control approach shown here can beuseful to meet the LVRT requirements, as will be discussedin Section VI. For unbalanced conditions, neglecting the zero-sequence components in the system, the stator and currentvoltage vectors can be written as [98], [103]

vs = v1sejωet + v2se

−jωet (19)

is = i1sejωet+φ1s + i2se

−jωet+φ2s . (20)

The voltage and current vectors at the output of the GSC (seeFig. 11) can be written as

vf = v1fejωet+φ1f + v2fe

−jωet+φ2f (21)

if = i1fejωet+φ3f + i2fe

−jωet+φ4f (22)

where the subscripts “1” and “2” are used to indicate signals ofpositive and negative sequences, respectively. Angles ∅if and∅is indicate a phase angle shift with respect to the stator voltageangle. The active and reactive power supplied by the DFIG tothe grid can be calculated from [29], [42], [103]

S = ktransf(vf i

cf + vsi

cs

). (23)

In (23), the superscript c is used to indicate the complexconjugate operator.

It is relatively simple to show that the active power andreactive power of (23) have three terms: the mean value, a termproportional to sin(2ωet), and a term proportional to cos(2ωet)[98], [101], [102], [110]. This can be written as

P =Pavg + Psin(2ωet) + Pcos(2ωet) (24)

Q =Qavg +Qsin(2ωet) +Qcos(2ωet). (25)

Using (19)–(25), several control targets for the operation ofDFIGs in unbalanced grids can be defined [29], [42], [98],[101], [103], [110]. For instance, in [103], one of the followingcontrol targets is proposed:

• To eliminate the oscillations in the total active power out-put from the overall system, i.e., Psin(2ωet) + Pcos(2ωet)

in (24);


• To reduce the oscillation in the total reactive powersupplied to the network, i.e., Qsin(2ωet) +Qcos(2ωet) = 0in (25).

• To supply a grid current with no negative-sequencecomponent, i.e., i2se−jωet+φ2s + i2fe

−jωet+φ4f = 0 [see(20) and (22)].

Each power converter has four degrees of freedom allowingthe independent regulation of the α–β (or d–q) componentsof the negative and positive-sequence output currents. In somepapers related to the control of DFIGs connected to unbalancedsystems, only one of the converters is used. For instance, in[6], the GSC is used to compensate the negative-sequencecurrent of the load. On the other hand, in [29], [42], [88], [89],[94], and [99], only the RSC is used to compensate the gridunbalance. DPC [29], [42] and d–q control are proposed inthese publications to compensate the grid unbalance, injectingnegative-sequence currents in the rotor.

In recent papers, the control of both the GSC and the RSChas been proposed to compensate the grid unbalance. This hasthe advantage that additional degrees of freedom are introducedin the control system by using two power converters, and morecontrol targets can be achieved [98], [101]–[103], [111], [112].

IV. SENSORLESS CONTROL OF DFIGs

The DFIG can be used as a variable-speed generator in stand-alone and grid-connected applications [95], [113]–[116]. Inboth cases, the use of sensorless vector control is desirablebecause position encoders or speed transducers have manydrawbacks in terms of maintenance, cost, robustness, and ca-bling between the speed sensor and controller [78].

There are several sensorless methods reported in the litera-ture. In this paper, they are classified as open-loop sensorlessmethods, model reference adaptive system (MRAS) observers,and other sensorless methods. Most of the sensorless controlmethods reported here have been applied to conventional vec-tor control of DFIGs (see Section II-C). However, sensorlessschemes can also be applied to the control methods discussedin Section II-D and E.

A. Open-Loop Sensorless Methods

Most of the early work in sensorless control of DFIGs isbased on open-loop methods, where the estimated and mea-sured rotor currents are compared in order to derive the rotorposition [117]–[121]. For instance, the rotor current referred tothe stator can be estimated using the stator flux and the statorcurrent as [121]

ι̂sr =(ψ

s− Lsι̂s)

L0. (26)

The measured rotor current can be referred to the stator using

isr = (irα + jirβ)e−jθsl (27)

where the slip angle is defined in (5).

Fig. 12. Block diagram of a typical MRAS observer.

In (26) and (27), isr is the rotor current vector referred to thestator, and (irα + jirβ) is the measured rotor current in α–βcoordinates. Using (26) and (27), an estimation of the slip angleis obtained as

θ̂sl = tan−1(irβ/irα)− tan−1(isrβ/i

srα

). (28)

Using (28) in (5), an estimation of rotor position angle isderived. Open-loop methods are not only based on estimationof the DFIG rotor current vector. In [122], an observer basedon the magnetizing current derived from the rotor and statorequations of the machine is proposed, although only simulationresults were presented, and no methodology was proposedfor the observer modeling and design. In [123], a rotor-flux-based sensorless scheme is proposed, where the rotor fluxis obtained by integrating the rotor back electromotive force.This sensorless method has poor performance when the ma-chine is operating around the synchronous speed becausethe rotor is excited with low frequency voltages. Therefore,the rotor flux cannot be accurately estimated by integrating therotor voltages.

In the open-loop methods, the rotational speed is obtainedvia differentiation of the estimated slip angle of (28), which canamplify the high frequency noise. Moreover, for the open-loopmethods reported in the literature, issues of observer modeling,observer bandwidth, and design methodology for the wholesensorless system are not discussed.

B. Sensorless Method Based on MRASs

The MRAS was first introduced for sensorless control of cageinduction machines in [124]. In this publication, the observerdesign is discussed, and a small-signal model is proposed. Mostof the MRAS observers proposed in the literature for cageinduction machines are based on rotor flux estimation.

The application of MRAS observers for sensorless control ofDFIGs was first reported in [125] and [126]. However, in thesepapers, only simulations were presented for a DFIM operatingat very low rotational speed. Issues such as observer dynamics,control design procedure, sensorless accuracy, and sensitivityto machine parameter variations were not addressed. Furtherpublications discussing the application of MRAS observers forsensorless control of DFIGs were presented in [127] and [128].

In the general case, an MRAS observer is based on twomodels [61], [77], [124], [129]–[134]: a reference model andan adaptive model (see Fig. 12). The estimated speed and rotorposition are used to adjust the adaptive model, driving the error


Fig. 13. (a) Stator-flux-based MRAS observer proposed in [127]. (b) Small-signal model corresponding to the stator-flux MRAS observer.

ε to zero. This error is usually defined as the cross productbetween reference vector x and derived estimated vector x̂.Mathematically, this can be written as

ε = x̂dxq − xdx̂q = |x||x̂| sin(θε) (29)

where θε is the phase angle between the vectors (x̂, x). In[115], the small-signal model, machine parameter sensitivity,and the design procedure of a stator-flux MRAS observer werepresented (i.e., x = ψ

s). In this case, the reference model and

the adaptive model are obtained, respectively, as

ψs=

∫(vs −Rsis)dt (30)

ψ̂s=Lsis + L0ire

jθ̂r . (31)

The estimated rotor position angle θ̂r is used to drive theerror of (29) to zero. The implementation of the stator-fluxMRAS observer is shown in Fig. 13(a), and the small-signalmodel corresponding to this observer is shown in Fig. 13(b).As shown, the gain of the feedforward path is dependent on themagnetizing current idr0. Therefore, if the DFIG is operatingin a grid-connected application and if the magnetizing currentrequired for the generator is entirely supplied from the grid,then the rotational speed cannot be tracked by the observer.

The experimental result depicted in Fig. 14 further corrobo-rate the small-signal model in Fig. 13(b) [133]. The DFIG is asensorless vector controlled using a stator-flux MRAS observer;when t = 23 s, the magnetizing rotor current ird0 is driven tozero and the system becomes unstable because tracking of therotor position angle and rotational speed is lost.

In [61], [136] a rotor current MRAS observer (RCMO) isproposed, which is appropriate for grid-connected and stand-alone operation for most of the DFIG operating range. Inthis case, the reference “model” is simply the measured rotorcurrent. The adaptive model is derived from (26) and can bewritten as

ι̂r =(ψ

s− Lsι̂s)

L0ejθ̂sl . (32)

Fig. 14. Sensorless control of a grid-connected DFIG using a stator-flux-based MRAS observer. Notice that the control system is unstable when therotor magnetizing current idr0 is driven to zero.

Fig. 15. (a) RCMO presented in [61]. (b) Small-signal of the RCMO pre-sented in [61].

A detailed description of the RCMO, including the method-ology required to synchronize the DFIG to the grid, the small-signal model, and the control algorithm used for catching thespeed on the fly, is presented in [61]. The implementation ofthe RCMO is shown in Fig. 15(a). Fig. 15(b) shows a linearizedmodel of an RCMO, which is used to design the PI controllerin Fig. 15(a).

Experimental results obtained with a DFIG vector controlledusing a sensorless scheme based on an RCMO are shown inFig. 16. Fig. 16(a) shows the performance of the control systemused to synchronize the DFIG to the electrical grid before thegrid-connected generation is started. Notice that, in t = 20 s,the power switch is closed, and the DFIG stator is connectedto the grid. Fig. 16(b) shows the experimental results obtainedfor speed catching on the fly with sensorless control using theRCMO. These experimental results are fully discussed in [61]and [136].

From the small-signal model in Fig. 15(b), it is concludedthat the gain of the feedforward path is only affected by themagnitude of the rotor current vector, which is not zero in thetypical operation range. Therefore, unlike the stator-flux MRASobserver, the RCMO can be applied to sensorless control ofDFIG when the machine is grid connected and entirely magne-tized from the stator. In fact, the RCMO can be applied to stand-alone and grid-connected application. In addition, as presentedin Fig. 16(a), sensorless vector control of the DFIG using anRCMO is appropriate to synchronize the DFIG to the grid.


Fig. 16. Experimental results discussed in [61] and [136] corresponding to theoperation of a RCMO. (a) Synchronization to the grid. (b) Speed catching onthe fly.

Considering that the RCMO is able to operate in most of theconditions required, i.e., grid-connected operation, stand-aloneoperation, etc. [133], it is considered that the MRAS observerhas the best overall performance among the three sensorlesstopologies discussed in that publication.

A variation of the RCMO is presented in [132]. Because theerror of (29) is a nonlinear function, in [132], it is proposed tocalculate the error using

ε = tan−1 ([ι̂r ⊗ ir]/[ι̂r.ir]) (33)

where ι̂r ⊗ ir represents the cross product between the rotorcurrent and that estimated using a Luenbenger observer [132],[137], [138]. On the other hand, ι̂r · ir represents the innerproduct between both currents. The use of (33) as normalizederror, instead of (29), has the advantage of producing a linearmodel, where the error is proportional to the phase shift anglebetween (̂ι) and (ir), instead of being proportional to thenonlinear function sin(θε) [see (29)]. This simplifies the designof the PI controller in Figs. 13 and 15, enhancing dynamicperformance across the operating range.

The performance of the MRAS observers reported in theliterature depends strongly on the correct identification of theinductances of the DFIM. In particular, the implementation ofthe RCMO requires the correct identification of the magnetizingand stator inductances [61], [133], [136], [139]. For grid-connected operation of DFIGs, the stator voltage can fluctu-ate about ±10% of its nominal value, changing the level ofmagnetic saturation in the machine. Therefore, the magnetizing,stator and rotor inductances are subjected to variations. In orderto maintain the tracking of the rotor position angle, even inthe presence of grid-voltage fluctuations, adaptive tuning of thestator inductance is proposed in [139]. This algorithm is basedon the fact that the magnitude values of the estimated rotorcurrent and that measured by the transducers are equal when themachine parameters are correctly tuned, i.e., when |ir| = |̂ιr|;then, Ls = L̂s, and L0 = L̂0(|̂ι|) is the rotor current vector esti-mated from (32) (see [61]). The experimental results discussed

in [139] show that the variation in the stator inductance can becompensated when the proposed adaptive algorithm is properlydesigned.

A new sensorless control topology, which is also based onthe MRAS observer, is presented in [131] and [135]. Theproposed observer is called the torque-based MRAS observer(TBMO) and uses a different methodology for estimating therotor current vector. Assuming that the vector control systemis orientated along the stator flux, then the torque and fluxcomponents of the rotor current vector can be calculated as

irq =L̂s

L̂0

|ψs⊗ is|

|ψs| =

L̂s

L̂0

Te

|ψs| (34)

ird =

[√(i2rα + i2rβ

)− i2rq

]1/2

. (35)

The d–q components of the rotor currents calculated using(34) and (35) are the reference model of the MRAS observer.Note that the torque and flux rotor currents of (34) and (35) canbe calculated from the α–β components of the stator flux andmeasured stator/rotor currents.

According to [135], the main advantage of the proposedTBMO is that (34) and (35) can be used directly as feedbacksignals of the control system, increasing the dynamic responseand improving the stability of the whole system. Note that (34)and (35) are not affected by errors in the rotor position angle.

C. Other Sensorless Methods for DFIMs

Sensorless control of DFIGs based on PLLs is proposed in[141]–[143]. As discussed in [124], the operating principle ofPLLs is similar to MRAS observers because the error of (29)and (33) are driven to zero when the phase shift between theestimated vector and the reference vector is null. Therefore, thesensorless observers of [141]–[143] have a similar performanceto those reported in [133]. However, some issues, such as thedesign of the PI controller located in the PLL system and thebandwidth of the rotor position observer, are not addressed in[141] and [142].

Sensorless control of DFIMs is also discussed in the paperreported in [144]–[147]. In [146] and [147], a rotor positionobserver similar to the RCMO of [61] is discussed. The PI con-troller (see Figs. 13–15) is replaced by a hysteresis controller.The authors claim that this controller improves the performanceof the observer because the design of the hysteresis controllerdoes not require good knowledge of the plant parameters. How-ever, as it is well known, controllers based on hysteresis mayproduce signals of variable frequency at its output. Therefore,some knowledge of the plant is usually required in order tomaintain this frequency inside a given operating range.

In [144] and [145], a rotor position observer, which is basedon the air-gap active and reactive power, is proposed. Thisalgorithm has some similarities to the TBMO reported in [135]because the torque and flux components of the rotor currentare calculated using the α−β components of the measuredvoltage and currents without requiring an estimation of the


rotor position angle. Assuming a stator-flux orientation, thed−q components of the rotor current can be calculated as

ι̂dr =Pg

|vs −Rsis|ι̂qr =

Qg

|vs −Rsis|(36)

where Pg and Qg are the power transferred across the air gap.The current estimated using (36) are used in a RCMO in orderto estimate the rotor position angle. It is claimed in [144] and[145] that the main advantage is that the calculation of thestator-flux vector is not required in the vector control system.However, in order to calculate Pg and Qg , an estimation of theiron losses and magnetizing reactive power is required [144].This can produce some errors, particularly when the DFIM isoperating with light loads.

Sensorless control of DFIMs can be also achieved using sig-nal injection [148]. This methodology is relatively well knownfor cage induction machines [149]. However, to the best of ourknowledge, sensorless control of DFIMs using signal injectionhas only been discussed in [148]. The operating principle isthat the DFIM is a transformer in which the relative positionbetween the primary and secondary winding changes as therotor rotates. Therefore, if a high-frequency signal is injectedinto the rotor, the phase of the corresponding signal in the statorhas a component that is dependent on the rotor position angle.The main advantage of this method is high robustness againstvariation in the machine parameters. However, experimentalvalidation of this method has not been reported, and injectionof high-frequency signals in the DFIG rotor is not simple toachieve in relatively large machines, such as the ones used forwind power generation.

To the best of our knowledge, the performance of the re-viewed sensorless methods has not been studied for operationin unbalanced grids or when the DFIG is feeding a stand-aloneunbalanced load of linear/nonlinear nature. Moreover, sensor-less control of DFIGs during LVRT conditions has not beenaddressed in the literature. Further research in these subjects isrequired.

V. FREQUENCY SUPPORT USING DFIGs

As wind power penetration increases, the fluctuating behav-ior of the wind velocity has more impact on the grid frequency.Wind energy penetration may increase during periods of lowloads, e.g., in the night. In this case, grid-frequency fluctuationsabove the maximum allowed by the grid codes can be produced[150]–[152] if conventional MPPT is used to control the powergenerated. In some countries, such as China [153], [154], about27% of the yearly wind energy is curtailed because most windfarms are operating using MPPT control without frequencyregulation [153]. In the past, the control used was based ondisconnecting part of the wind farm. Now, modern controlmethods based on droop control and inertia emulation arepreferred [155].

Grid connection requirements (GCRs) are introducing regu-lations to establish grid-frequency support from wind turbines[156]. For instance, according to the E-ON GCR [157], whenthe frequency exceeds the value of 50.2 Hz, wind farms mustreduce their active power with a gradient of 40% of the available

power per hertz, with a ramp rate of 10% of the grid connectioncapacity per minute. A more detailed description about theGCRs is found in Section VI-A.

There are several publications related to the subject of grid-frequency support using wind energy systems [153]–[155],[158]–[170]. Most of the proposed methods use the kineticenergy stored in the wind turbine rotating mass to provide addi-tional power to the system in case of grid-frequency variation.

In power systems, inertia constant H is used instead ofinertia J . Constant H is defined as [155]

H =Ek

S=

Jω2r

S(37)

where S is the nominal apparent power of the WECS, and Ek

is the kinetic energy stored in the rotating blades. As shown in(37), H is equal to the time that a WECS can supply the nominalpower using the kinetic energy stored in the rotor. The inertiaconstants for WECSs are in the range of 2–6 s, whereas H fora typical power system generator is in the range of 2–9 s [155].

Frequency support is usually accomplished using inertiaemulation and/or droop control. The output power of the DFIGis controlled as a function of the grid frequency, i.e.,

P ∗out = Prefω +Kd(fgrid − fref) +Kei

d(fgrid)

dt(38)

where Prefω represents the output power demand for nor-mal steady-state operation of the power system when thegrid frequency fgrid is equal to the reference frequency.This power demand might be obtained, for instance, from alookup table, where a relationship between the rotational speedand the demanded output power is stored. The second termKd(fgrid − fref) represents the droop power. In a typicalsystem, when the power is unbalanced, (e.g., there is moreor less consumption than power generation) the grid fre-quency changes. In this case, the DFIG output power is in-creased/decreased in order to support the generation. The lastterm Kei(d(fgrid)/dt) corresponds to the inertia emulation. Inthis case, the power demand is varied according to the rateof change of the grid frequency. This component emulatesthe inertia response of a conventional synchronous machine.Assuming stator-flux regulation, reference power P ∗

out is reg-ulated using the quadrature rotor current in a DFIG, which iscontrolled by the RSC.

To implement (38), the variable-speed WECS must have apower reserve. Depending on the operating point, a combina-tion of speed control and pitch control has been used to maintainthis reserve [153], [166]–[169]. In [79], the operating range isdivided into low-, medium-, and high-wind-speed sectors.

At low wind speed (e.g., 0 < V < V3 in Fig. 17), thesteady-state system is operating at a suboptimal power line,for instance, at 90% of the maximum power curve shown inFig. 17. When the frequency decreases below fref , the gen-erated power is increased by decreasing the rotational speeduntil the maximum power point is reached (located in the curvePout = Koptω

3r ). If the grid frequency increases above fref , the

captured power is reduced by increasing the rotational speed.At medium wind speed (e.g., V3 < V < V5 in Fig. 17), a

combination of speed control and pitch control is used. When


Fig. 17. Optimal and suboptimal power curve for the control strategy pro-posed in [79].

the turbine velocity reaches maximum speed, pitch control isactivated to avoid overspeeds.

At high wind speed, the power is regulated mainly by pitchcontrol. In this case, the output power is controlled below thenominal value in order to maintain a power reserve, which isused when the grid frequency goes below the reference value.A control system for frequency support, also dividing the windspeed into three operating areas, is presented in [167] and [169].The main difference to that discussed in [79] is at low windspeed; here, it is suggested to regulate the output power linearlywith the rotational speed, i.e.,

P ∗out = kωr. (39)

According to [171], smoothed power generation could beobtained when the rotational speed is linearly changed with thepower.

The application of variable-speed WECSs based on DFIGsfor frequency and voltage regulation in microgrids and mini-grids has also been discussed [159], [172]–[174]. In this case,the DFIG stator voltage is regulated according to

fs = kp(P∗ − P ) (40)

Vs = kq(Q∗ −Q) (41)

where fs and Vs are the frequency and stator voltage of theDFIG and kp and kq are the droops. A control system similarto that proposed in [159] is shown in Fig. 18. The magnetizingcurrent supplied from the RSC is regulated to control the statorvoltage, and the stator frequency is varied according to (40).An energy storage system (ESS) is used to supply power to thegrid or absorb excess power captured from the WECS. Whenthe ESS is fully charged, pitch control is required to limit thepower transferred to the grid.

VI. LVRT WITH DFIGs

A. GCRs

In the last two decades, the installed wind power capacity hasconsiderably grown. At the end of 2011, the total installed windpower world capacity reached 238.5 GW [175]. At the same

Fig. 18. Control system similar to that proposed in [159] for the operation ofDFIGs in microgrids.

time, wind energy penetration into the grid has significantlyincreased. A good example is Spain, where the average windenergy penetration has been 11%, 13.8%, and 16% in 2008,2009, and 2010, respectively [176]–[178], although the windpower penetration can temporarily reach a much higher value,e.g., the 64% experienced on September 24, 2012 [179] in theSpanish grid.

The GCRs are set by the power system operators to ensurethe reliability and efficiency of the utility [156], [180]. Theserequirements can be divided into two main classes: steady-state or quasi-stationary operation requirements, and LVRTrequirements. A review of the GCRs of several countries ispresented in [156].

In steady-state or quasi-stationary operation, the require-ments such as reactive and active power regulation to supportthe utility voltage and frequency are specified in the GCR, andhave been dealt with in part in Section V.

Under grid disturbances, the former GCRs allowed the dis-connection of the WECSs to avoid large overcurrents. However,with the increase in the wind energy penetration, the suddendisconnection of WECSs can lead to instability of the entirepower system [181], [182]. In this scenario, the power systemoperators have updated their GCRs, and the wind generators arerequired to remain connected to the grid during disturbances asit is standard for conventional generators [156], [157], [180],[183], [184].

With the current GCRs, the LVRT requirement demandswind power plants to remain connected when a grid-voltagesag occurs, thus contributing to maintaining stable networkvoltage and frequency by delivering active and reactive powerto the grid with a specific profile depending on the grid-voltagedip depth. Hence, LVRT is probably the most challengingrequirement among the GCRs, at least from the point of viewof the WECS.

LVRT requirements, extracted from the GCR of the utilityoperator E-ON [157], are shown in Figs. 19 and 20. Verysimilar curves are provided in the LVRT requirements of otherpower systems operators [156], [180], [183], [184]. When a


Fig. 19. Voltage limit curve to allow generator disconnection.

Fig. 20. Reactive current to be delivered to the grid under a voltage dip.

grid-voltage sag appears, the power generation plant mustremain connected to the grid if the line voltage remains overthe limit line 1 in Fig. 19 (region A). In certain cases, a briefdisconnection is allowed if the line voltage lies between thelimit-lines 1 and 2 (region B). Here, resynchronization typicallywithin 2 s is required to ensure a minimum reactive powersupply during the fault; also required is an active power increaserate of > 10% of the rated generator power per second afterfault clearance [157]. A brief disconnection is always allowedin region C, where resynchronization times of more than 2 sand an active power increase following fault clearance of lessthan 10% of the rated power per second are also possible inexceptional cases. If the grid voltage remains low for longerthan 1.5 s (region D), selective disconnection of generatorsdepending on their condition can be carried out by the gridprotection system [157], [185]. In addition, during the voltagesag, the WECS has to deliver a reactive current, specified inFig. 20, to aid the utility in holding the grid voltage. Thereactive power to be injected depends on grid-voltage reductionduring the dip, the system rated current, and the reactive currentgiven to the grid before the dip appears.

B. DFIG Behavior Under Grid Fault

A number of studies concerning the impact of grid faultson DFIGs have been reported. For the grid, symmetrical dis-turbances, particularly the deep voltage sags, can be seen asmore stressing than asymmetrical disturbances since all phasesare lost. However, the analysis for asymmetrical disturbances ismore complex due to the appearance of negative-sequence com-ponents in the voltages and currents [3], [186]–[188]. DFIGshave low negative-sequence impedance, and small negative-sequence stator voltages can lead to high stator currents [106].

Fig. 21. Machine model from the rotor side.

Most of the disturbances are asymmetrical. Only 12% of griddips are symmetrical [189], [190].

As shown earlier, conventional regulation for the DFIG isachieved by controlling the rotor currents. The machine modelseen from the rotor side is shown in Fig. 21 [182], [186],[188], [191], where σ = (1− L2

0/LsLr). To control the rotorcurrents by the RSC voltage, it is useful to calculate the open-circuit rotor voltage vrr0. Note that superscript “r” denotes thevariables expressed in the rotor reference frame.

Considering the Park model for the induction generator(1)–(3) and the rotor in open circuit, the expression for the statorflux is

d

dtψs= vs −

Rs

Lsψs

(42)

where the stator voltage can be expressed as the sum of thepositive (v1s), negative (v2s), and zero (v0) sequences

vs = v1sejωet + v2se

−jωet + v0. (43)

The solution for (42) is shown in (44). The zero-sequencevoltage does not create flux [188], [191]. From (44), the ex-pression for the open-circuit rotor voltage shown in Fig. 21 canbe obtained, as shown in (45), which is given in the following:

ψs=ψ1se

jωet + ψ2se−jωet + ψn0e

−t/τs

=v1sjωe

ejωet +v2sjωe

e−jωet + ψn0e−t/τs (44)

vrr0 = v1sL0

Lssejsωet + v2s

L0

Ls(s− 2)e−j(2−s)ωet

+L0

Ls

(1

τs+ jωr

)ψn0e

−t/τsejωrt . (45)

In normal operation, the grid voltage presents only the posi-tive sequence, and the second and third terms in (44) and (45)are zero. However, when a grid-voltage sag appears, the flux isexpressed as the sum of three components [182], [187], [188],[191]: 1) the nonhomogenous or forced flux composed by twoterms corresponding to the positive- and negative-sequencestator voltages; and 2) the homogenous or natural flux.

The natural flux vector does not rotate. This is a transient dccomponent flux that exponentially decays with time constantτs = Ls/Rs and initial value ψn0, which depends on the typeand depth of the grid-voltage sag and, in case of asymmetricaldips, on the instant of time within the grid-voltage period inwhich the grid disturbance occurs [182], [191].

The forced flux is the sum of the positive-sequence flux thatrotates at synchronous speed and the negative-sequence flux[86]. The difference between asymmetrical and symmetrical


TABLE IIIPOSITIVE, NEGATIVE, AND NATURAL FLUXES (PER UNIT)

FOR DIFFERENT TYPES OF FAULTS [191]

voltage sags is the presence or absence of the negative-sequencevoltage and flux.

With respect to the rotor, as shown in (45), the open-circuitrotor voltage has three components: 1) the positive-sequencevoltage rotating at sωe (the only component that is present inbalanced operation); 2) the negative sequence that rotates atalmost twice the synchronous speed (2− s)ωe and that onlyappears when the disturbance is asymmetrical; and 3) the rotorvoltage produced by the natural flux that creates an open-circuitvoltage rotating at ωr.

When a grid disturbance occurs, the open-circuit rotor volt-age has a large transient overvoltage (mainly caused by thenatural flux), which can be even greater than the stator voltage[156], [182]. Because of the transient nature of the natural flux,during symmetrical disturbances, the rotor voltages return topositive-sequence values even if the grid fault is permanent [see(45)]. During asymmetrical faults, however, the rotor voltagealso has a large and permanent negative-sequence component[see (46)], and the rotor voltages are higher and more damagingthan those for symmetrical grid dips [191].

Table III shows the per unit (p.u.) values of the positive-sequence, negative-sequence, and natural fluxes in (44) as afunction of the grid fault type and the depth of the voltage sagd in p.u. (i.e., for a three-phase voltage sag where the voltagefalls from 1 to 0.2 p.u., the d value is 0.8). The natural fluxvalue depends on the time instant within the voltage periodwhere the fault occurs. The phase-to-phase fault presents thehighest natural and negative-sequence flux, and the highestovervoltages in the rotor windings [191].

The maximum amplitude of the transient rotor voltage isgiven in (46) for a symmetrical fault [182]. A discussion of themaximum rotor voltage amplitude produced by an asymmetri-cal fault [see (47)] is reported in [99]. As shown in Table III and(44), deeper voltage sags lead to higher transient voltages,and larger dip asymmetry increases negative-sequence voltagesand the maximum rotor voltages, as shown in the following,respectively:

(vro_transient)max ≈ L0

Ls(|s|(1− d)v1s + (1− s)dv1s) (46)

(vro_asym)max ≈ L0

Ls

|sωe| · v1s + |(s− 2)ωe| · v2sωe

. (47)

Without specific control action, the rotor overvoltages pro-duce high ac rotor currents with synchronous frequencies su-perposed upon the low-frequency steady-state rotor currentsinjected by the RSC [156], [182], [192]. The rotor overcurrentmay exceed 2–3 times the nominal rotor current, which is notacceptable [192]. On the stator side, these currents appear as dccomponents [192], [193].

The higher rotor currents lead to rising dc-link voltage [156],[192], [194]. If the system in Fig. 1 is assumed, the GSCcontroller intends to regulate the dc-link voltage to its nominalvalue, causing a GSC overcurrent of up to 1.5 times the nominalvalue. Even with GSC control action, the dc-link voltage canreach values of about 2–3 times higher than the nominal dc-linkvoltage, beyond the limit of the dc-link capacitor [192].

The positive-sequence flux produces a similar torque behav-ior to that of the balanced operation, but the negative-sequenceflux tends to create motoring action that results in an increase intorque pulsation at twice the synchronous frequency [89], [99],[191] and a reduction in the average torque [195]. The presenceof the second harmonic in the electromagnetic torque can causeundesired mechanical oscillations, reducing the turbine lifespan and creating higher acoustic noise [89], [195].

During the grid disturbance, there is a mismatch betweenthe mechanical and electromagnetic torque that leads to rotoroverspeed [196]. However, this is not too significant since therotor inertia acts as a storage system for the energy surplus, anda certain increase in speed (10%–15%) is acceptable [156].

An induction machine fed by unbalanced voltages producesunbalanced flux [191] that can lead to unexpected magneticsaturation, excessive heating, and reduced generator lifetime[195]. Moreover, it will draw unbalanced currents that willincrease the grid-voltage unbalance and cause overcurrent prob-lems [89].

Immediately after the voltage sag clearance, the sudden changein the stator voltages causes the natural flux [182] to appear again.This causes the electromagnetic torque to oscillate, causingincreased stress on the turbine shaft [192].

C. Systems and Control for LVRT Compliance With DFIG

As stated earlier, the grid disturbances cause rotor overcur-rents and overvoltages together with a dc-link overvoltage thatcan lead to converter failure if no protection is included [182],[191], [192], [197]. Different protection devices are depicted inFig. 22. Their operation and some control approaches to complywith the LVRT requirements will be discussed here.

The initial solution implemented by manufacturers to protectthe rotor and the converter was to short-circuit the rotor wind-ings with the so-called crowbar and to disconnect the turbinefrom the grid [198], [199]. This solution is not allowed withthe LVRT requirements set at the current GCRs because theWECSs do not support the utility to resume normal operation.

If the RSC is sized to generate a voltage equal to the rotorovervoltages of (46) and (47), it will be able to fully controlthe rotor currents [182], [186], [191]. This is the best solutionto deal with rotor overvoltages because it allows full controlof the DFIG at all times. To achieve it, overmodulation in theRSC would be required [200], in spite of the increased rotorcurrent harmonics. A method to design the RSC size based onthe maximum rotor overvoltage and overcurrent is presentedin [90]. One of the most extensive analysis of the operationlimits for the RSC under grid disturbance is presented in [201],which considers the impact of limited ratings for the GSC andRSC during grid disturbances. Oversized converters allow morecontrollability, but the DFIG topology loses its advantages of


Fig. 22. Rotor and converter protection devices: crowbar, dc-link chopper, ESS, and ac switch [156], [213].

the low-size power converter [182]. It is well known that theconverter is sized to manage ≈30% of the total DFIG power[3], [181], [202] and is not normally rated to generate a voltageequal to the rotor overvoltages [182]. It is also noted that, fordeep grid-voltage sags, the RSC oversizing is far beyond theconverter steady-state ratings. Converter sizing is thus a tradeoffbetween the LVRT requirements and the cost, together withother protection elements such as the crowbar and the dc-linkchopper.

DFIGs are always equipped with a crowbar, as shown inFig. 22, which is a device that short-circuits the rotor windingsthrough resistors, thereby limiting the rotor voltage and provid-ing an additional path for the rotor current [185]. Two crowbaroptions are available [156]. The first option is the passivecrowbar implemented with a diode rectifier or two thyristors inantiparallel. This implementation requires the crowbar currentto be forced to zero to deactivate the device, and full controlover the crowbar deactivation is not possible. The second optionis the active crowbar using IGBT switches; this allows crowbardeactivation and, consequently, faster recovery of the DFIGcontrol. The crowbar resistance value affects the rotor andcurrent behavior [197]. Large crowbars result in better dampingof the rotor and stator overcurrents, and the torque overshoot.It also reduces the reactive power consumption. However, verylarge crowbars can cause current spikes upon deactivation and ahigh voltage at the rotor slip rings, resulting in voltage stress onthe rotor windings [193], [194]. In [194], Kasem et al. suggesta crowbar resistance of 0.3 p.u. if the maximum rotor voltageis limited to 1.2 p.u. The calculation of the crowbar resistanceusing

(Rcrowbar)max =

√2(vr)maxωeL

′s√

3.2V 2s − 2(vr)2max

(48)

is discussed in [193], where (vr)max is the maximum allowablerotor voltage, L′

s = Ls + LrL0/(Lr + L0), and Vs is the statorvoltage.

Upon activation of the crowbar, the RSC can be switchedoff [192], [194], [203]. However, the rotor currents continue

to circulate to the converter dc-link through the freewheelingdiodes of the RSC, leading to a very fast dc-link voltageincrease and a possible activation of the dc-link chopper to limitthe dc-link voltage value [192], [203].

During crowbar operation, rotor currents are not controlledby the RSC, and the machine acts as a single-fed inductiongenerator with rotor resistors. The machine consumes reactivepower that can contribute to deepening the grid-voltage sag[203]. The GSC must supply the grid with reactive power, asdemanded by the LVRT requirements, and the reactive powerto the machine [204], [205]. In [194], it is proposed to connectthe GSC and the RSC in parallel, using suitable ac switches, tosupply more reactive power to the grid.

If the DFIG is not able to supply the reactive power sup-port required by the GCR, dynamic VAR compensators, staticVAR compensators [206], or static synchronous compensators[207]–[210] can be installed at the DFIG terminals to provideit. Other equipment, such as the dynamic voltage restorer, canalso be used [211].

After the fault clearance, transient rotor overvoltages appearagain, and the system experiences a disturbance similar to thatof the initial fault. This would require a crowbar [or dc-linkchopper activation (see Fig. 22)] for a second time [192], [194].

Unlike asymmetrical disturbances, symmetrical grid distur-bances only cause transient rotor overvoltages, and the crowbarmode is active until the rotor currents die down. After this,the crowbar is disconnected, and the RSC is started again tocontrol the rotor currents. Since the fault is still present, theactive power reference is reduced to avoid overload. The DFIGcan contribute to the reactive power support to the grid. Notehowever that reactive power support is provided by the GSCthroughout the crowbar mode period [192], [204], [212]. In[214], the crowbar is disconnected when the rotor currents fallbelow a threshold value instead of reaching zero, reducing thecrowbar mode time.

The dc-link chopper [156], as shown in Fig. 22, is anotherprotective device to keep the dc-link voltage within acceptablelimits. It can concurrently operate with the crowbar [156],[192], [203]. The dc-link chopper is not essential for fault


ride-through operation, but it increases the range of DFIGoperation [192], [203]. The ESS [213], [215] connected tothe dc-link absorbs the extra energy supplied to the dc linkand returns it to the DFIG in normal operation. However, itsignificantly increases the complexity and cost of the WECS.A good performance comparison using a crowbar, a dc-linkchopper, and ESS methods is found in [213].

The stator switch shown in Fig. 22, [156], [185], [216]is another device to meet the LVRT requirements. The sta-tor is disconnected for a short period using this switch; theRSC is blocked, and the generator is demagnetized. After theRSC is restarted, the stator is reconnected, and the operationis resumed. During stator disconnection, the GSC suppliesreactive power to the grid. This implementation limits thetransient magnitude and duration and keeps full control overthe generator during the largest part of the disturbance interval[156], [216].

As discussed earlier, there is a mismatch between the elec-tromechanical torque and the mechanical torque in the presenceof the grid disturbance. Pitch control can also be used to reducethe mechanical torque [156], [192] to avoid rotor overspeed.However, pitch control can change the blade angle at a rela-tively slow rate [217], which is too slow to help the system torespond to a grid fault.

D. Control Methods for LVRT Compliance With DFIG

This subsection summarizes the control methods for LVRTcompliance. The goal is to control rotor voltages and currents,to reduce the rotor overvoltages and/or overcurrents, and toavoid the crowbar activation in order to keep full DFIG controlat all times to meet the LVRT requirements. However, inmany cases, the crowbar activation cannot be avoided, and thecrowbar mode concurrently works with the control method.

Some control approaches regulate rotor and GSC currentsin the positive and negative d–q reference frames [90], [98],[219]–[221] based on a positive- and negative-sequence modelsof the DFIG [99]. The main control goals cover the DFIGactive and reactive power to meet the LVRT requirements.As discussed in Section III-B, each power converter has fourdegrees of freedom, allowing to include additional control goalsas, for instance, the regulation of the dc-link voltage, statorcurrent balancing, and cancelation of the oscillations in theactive power, rotor current, and torque.

Although crowbar activation cannot be avoided in case ofsevere asymmetrical faults [90], a noncrowbar method to reducethe rotor overvoltages based on injecting demagnetizing fluxcurrents from the RSC is proposed in [33], [186], [221], and[222]. Full DFIG control is retained, but a large rotor currentcapacity is needed, and there is limited capability in the case ofasymmetrical faults. If the crowbar is activated, the use of thedemagnetizing current reduces the crowbar mode time [223].

A robust controller in the α–β stationary frame is presentedin [106], claiming full control in all LVRT cases. However, theresults have been obtained with an oversized converter that canaccommodate rotor overvoltages and full rotor current control.With a suitable-sized converter, this control method may havesome limitations.

Another control approach introduces a virtual resistance inthe rotor to reduce rotor overcurrents. A combination of demag-netization and virtual resistance control is found in [188]. Forsymmetrical dips, reduced rotor currents in comparison with[186] are reported. Operation under asymmetrical faults has notbeen reported.

A PI controller with a resonant compensator is presentedin [110], [224], and [225] for operation under distorted grid-voltage conditions. Although results seem promising, the LVRTissue is not addressed.

In [226] and [227], the conventional controller used in nor-mal operation is switched to a vector-based hysteresis cur-rent controller during grid faults. Good system performanceis achieved; however, the operation limits are not specified,and there are drawbacks to the hysteresis control: higher har-monic content, higher switching frequency or, if the maximumswitching frequency is limited, large error bands that producesignificant low-order harmonics.

Sliding control has been successfully applied to DFIG in[228] under unbalanced conditions and a harmonically distortedgrid. Future application of this control method to the LVRTproblem can be expected.

VII. CONCLUSION

This paper has summarized the most recent research inthe field of control systems for DFIGs in wind energy ap-plications. After reviewing the papers related to conventionalcontrol methods for DFIGs connected to balanced systems,it is concluded that vector control, typically orientated alongthe stator flux, is still the most adopted method for regulatingthe rotor currents of DFIGs. With this control methodology,decoupling of the reactive power and electrical torque is simpleto achieve. However, as discussed in Section II, most of thecontrol schemes presented in Section II-D–F can provide goodoverall performance.

Regarding sensorless control of variable-speed DFIGs, themost popular methods are based in MRAS schemes, with theRCMO providing good performance in both stand-alone andgrid-connected operation of DFIGs. The TBMO is also aninteresting method for sensorless vector control, particularlybecause the direct and quadrature rotor currents can be directlyobtained from the α–β components of the signals withoutresorting to transformations to a synchronous rotating axis.Concerning sensorless methods, more research can be requiredin some areas, particularly because the performance of the rotorposition observers proposed in the literature have not beenevaluated for LVRT operation.

In this paper, the control systems for the operation of DFIGsconnected to unbalanced grid or loads, have also been assessed.Several control targets for unbalanced operation have beenproposed in the literature, e.g., to eliminate the oscillationsin the total active power output from the DFIG, to reducethe oscillations in the total reactive power supplied to thenetwork, or to supply a grid current with no negative-sequencecomponents. To fulfill these control targets, the RSC and/orthe GSC can be used. The current trend is to use both power


converters simultaneously because more degrees of freedomsare available in this case.

Control systems for ancillary services and grid-frequencysupport have also been discussed in this paper. In the past,DFIGs where mostly controlled for MPPT operation. Nowa-days, it is expected that WECSs based on DFIGs can providedroop control and inertia emulation. This has been reviewed inthis paper.

Finally, in this paper, LVRT control systems for DFIGs havebeen discussed. The operation of the elements typically used forLVRT compliance, such as crowbars, choppers, static switches,and other elements, has been analyzed and extensively dis-cussed in this paper.

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Roberto Cárdenas (S’95–M’97–SM’07) was bornin Punta Arenas, Chile. He received the B.S. degreefrom the University of Magallanes, Punta Arenas, in1988 and the M.Sc. and Ph.D. degrees from the Uni-versity of Nottingham, Nottingham, U.K., in 1992and 1996, respectively.

From 1989 to 1991 and from 1996 to 2008, hewas a Lecturer with the University of Magallanes.From 1991 to 1996, he was with the Power Elec-tronics Machines and Control Group, University ofNottingham. From 2009 to 2011, he was with the

Department of Electrical Engineering, University of Santiago, Santiago, Chile.He is currently a Professor of power electronics and drives with the Departmentof Electrical Engineering, University of Chile, Santiago. His main researchinterests include the control of electrical machines, variable-speed drives, andrenewable energy systems.

Dr. Cárdenas was a recipient of the Best Paper Award from the IEEETRANSACTIONS ON INDUSTRIAL ELECTRONICS in 2005 and the “RamonSalas Edward” Award from the Chilean Institute of Engineers in 2009.

Rubén Peña (S’95–M’97) was born in Coronel,Chile. He received the Electrical Engineering degreefrom the University of Concepcion, Concepcion,Chile, in 1984 and the M.Sc. and Ph.D. degrees fromthe University of Nottingham, Nottingham, U.K., in1992 and 1996, respectively.

From 1985 to 2008, he was a Lecturer withthe University of Magallanes, Punta Arenas, Chile.He is currently with the Department of ElectricalEngineering, University of Concepción. His mainresearch interests include the control of power elec-

tronics converters, ac drives, and renewable energy systems.

Salvador Alepuz (S’98–M’03–SM’12) was bornin Barcelona, Spain. He received the M.Sc. andPh.D. degrees in electrical and electronic engi-neering from the Technical University of Catalo-nia (UPC), Barcelona, Spain, in 1993 and 2004,respectively.

Since 1994, he has been an Associate Professorwith the Mataró School of Technology (Tecnocam-pus Mataró-Maresme), UPC, Mataró, Spain. From2006 to 2007, he was with the Departamento de Elec-trónica, Universidad Técnica Federico Santa María,

Valparaíso, Chile, conducting postdoctoral research. In 2009, he was a VisitingResearcher for three months with the Department of Electrical and ComputerEngineering, Ryerson University, Toronto, ON, Canada. His research interestsinclude multilevel conversion and ac power conversion applied to renewableenergy systems.

Greg Asher (M’98–SM’04–F’07) received the B.Sc.and Ph.D. degrees from Bath University, Bath, U.K.,in 1976.

He is a Research Fellow in superconducting sys-tems with the University of Bangor, Gwynedd, U.K.In 1984, he was appointed as a Lecturer of con-trol with the University of Nottingham, Nottingham,U.K. In 2000, he was appointed as a Professor ofelectrical drives; in 2004, as a School Head with theSchool of Electrical and Electronic Engineering; andin 2008, as the Associate Dean for Teaching and

Learning with the Faculty of Engineering, University of Nottingham. He isthe author of nearly 300 research papers. He has received over £5 millionin research contracts and has successfully supervised 31 Ph.D. students. Hisresearch interests include motor drive control, cover power system modeling,power microgrid control, aircraft power systems, and motor drive systems,particularly the control of ac machines.

Dr. Asher was a member of the Executive Committee of the European PowerElectronics Association until 2003 and the Chair of the Power ElectronicsTechnical Committee of the IEEE Industrial Electronics Society until 2008.He is currently an Associate Editor for the IEEE Industrial Electronics Society.

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