1 Introduction

It has been estimated that power generation through wind will reach 300 GW until 2020, which is 20% of the whole energy production [1] The increasing demand for energy by society leads to scarcity of natural resources like coal, natural gas and oil [2] Renewable energy resources including wind, solar and dams are considered as everlasting forms of energy extraction methods but each method has certain limitations. However, wind energy and hydropower stations have many things in common and both of them can be synchronized together to get even a high amount of power.

While considering wind energy as a renewable energy source, the induction generator (IG) becomes really important. The conventional power plants utilize synchronous generator as they operate at synchronous speed and consumes high cost to regulate their speed by using a prime mover, mostly diesel engines and are the least cost-effective than induction machines. On the other hand, IG which is mostly self-exited can operate on variable speed even higher than synchronous speed [3] and are mostly suitable when connected by wind turbines.

The wind gyrators units use fixed and variable speed turbines [5], despite varying wind variable wind generators are opted to capture maximum power. Among all the variable speed generators double-fed generators (DFIG) coupled with the rotor side, power converters are now commonly available. Recently, the control of high performing induction machines has gained a lot of attention from industrial applications. The wind generator manufacturing companies are required to provide descriptive simulation model for their product [6]. Since this information is confidential and vendors do not provide such information, therefore, the mathematical modeling of such machines has attracted researches a lot in predicting the load characteristics and this is mainly due to the varying modes of operation including both steady-state and dynamic state [7, 8]. Much of the work has been done in simplifying the model, the impact of DFIG model simplicity was of main concern and the model stability was analyzed by neglecting resistance of rotor and stator [9].

The WTG model thus developed were validated by [10] and it showed the importance of distributed modeling in wind farm through IEC 61400-27 standard. Field-based measurement, the IEC Type-3 model for wind turbines based on voltage controller and wind power factor controller is verified in [11].

Although the current control based model has widely been used for DFIG modeling, but the model validation in previous works is carried out by using step input reference. However, it requires intensive analysis for various conditions when DFIG is connected to the grid under various modes. The IEC/WECC Type-3 WTG model is one of the benchmarks of the current–source model. The simulation-based DFIG model and its applications are described in [12] but still, it lacks the analysis.

In this paper, our contribution is to present the mathematical model analysis of wind turbines connected with the current control IG which is synchronized with the power grid station by implementing the DFIG controller to power electronics converters serving between the grid side and rotor side of IG. The power electronics converter model between the grid and the DFIG is based on the current control loop that monitors the speed of the wind turbine and its control through the current control strategy instead of just stepped input. The model of DFIG and its synchronization with the grid is also investigated through the synchronization of GSC and MSC and the back and forth power transfer in sub to synchronous and super synchronous operation in along with lab experiment.

This paper will be organized as follows. In Sect. 1 a brief history has been presented for the related work done on DFIG, Sect. 2 presents the mathematical model of wind turbine and suggests parameters for obtaining maximum mechanical power from a wind turbine and implements the mathematical model of DFIG, Sect. 3 presents the converter modeling strategy, Sects. 4 and 5 presents grid and machine side converters, Sect. 6 the simulation and experimental results for our proposed scheme and Sect. 7 concludes the whole discussion.

2 Wind Turbine Modeling and Integration with DFIG

The wind turbine shown in Fig. 1 is directly coupled with the rotor of the IG. The wind turbine extracts wind energy from the swept area of the rotor and transforms it into electrical energy. The mechanical power \(({P}_{m})\) delivered by the wind turbine is given by the following Eq. [13]

$${P}_{wind}=\frac{1}{2}A\rho {C}_{p}{{V}_{wind}}^{3},$$
(1)

where \(({C}_{p})\) is known as the coefficient of power, \((A)\) is the turbine’s blade swept area \(({\mathrm{m}}^{2})\), \((\rho )\) is the air density \((\mathrm{kg}/{\mathrm{m}}^{3})\) and \(\left({V}_{wind}\right)\) is the velocity of the wind in \((\mathrm{m}/\mathrm{s})\).

Fig. 1.
figure 1

Windmill connected to wind turbine

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The energy delivered by the turbine towards the IG rotor is given by the following Eq. [14]

$${E}_{wind}={P}_{m}\times t.$$
(2)

During power transformation, not all the power is delivered by the wind to the rotor. Since the energy remains conserved, therefore, using Betz theorem [14] the mechanical power can be obtained using the performance power coefficient ratio and is given by the following equation

$${C}_{p}=\frac{{P}_{m}}{{P}_{wind}}.$$
(3)

In Eq. (1) \({C}_{p}\) is not a constant but is a two-dimension dependent state function. One parameter is known as fractional tip speed \((\lambda )\) and other one is blade pitch angle \((\beta )\) and is expressed by using the following equation

$$\lambda =\frac{{\omega }_{r}R}{{V}_{wind}}.$$
(4)

Here, \({\omega }_{r}\) is the angular velocity (rev/min) of the turbine rotor and is controlled by using gearbox. The mechanical torque induced \(({T}_{m})\) by the wind turbine during rotation is given by the following Eq. (6) where \(({C}_{T})\) is termed as the torque coefficient and is given by Eq. (7)

$${P}_{m}={T}_{m}{\omega }_{r},$$
(5)
$${T}_{m}=\frac{1}{2}AR\rho {C}_{T}{{V}_{wind}}^{2},$$
(6)
$${C}_{T}=\frac{{C}_{P}}{\lambda }.$$
(7)

The state variables of power coefficient for VSWT [15] can be summarized by the following equation

$${C}_{p}\left(\lambda ,\beta \right)=0.73\left[\frac{151}{{\lambda }_{i}}-0.58\beta -0.002{\beta }^{2.14}-13.2\right]{e}^{18.4/{\lambda }_{i}}.$$
(8)

The mechanical power obtained from the wind turbine as a function of wind speed at various blade pitch angles is shown in Fig. 2. Similarly, the performance coefficient of the wind turbine termed as implicit function of the speed tip ratio is demonstrated in Fig. 3. The output characteristics curves in Fig. 2 reveal that in the beginning the output power drastically rises as the level of wind increases but then significantly drops to zero and the amplitude of turbine power also declines by increasing the pitch angle of blades. Similarly, the performance factor \(({C}_{P})\) at first increases but then starts to decline as the tip ratio crosses its knee value as shown in Fig. 3.

Fig. 2
figure 2

The turbine power delivered as a function of wind speed for different blade angles

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Fig. 3
figure 3

Performance coefficient factor as a function of the speed tip ratio for different blade angles

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The adopted model of DFIG is an analytical model of the following equations and the basic configuration is shown in Fig. 4 [14]. Where the induction machine works as a motor when the rotor angular velocity is less than synchronous velocity and works as a generator when the rotor angular velocity is greater than the synchronous velocity. The three-phase induction machine can be translated into a two axis synchronously rotating frame of reference using Clark and Park transformation theorems. The resulting frame of reference corresponds dynamic quadrature d-q with \(({\theta }_{e})\) synchronously rotating angle [13, 16]. Using the basic model of squirrel cage wound rotor type induction motor as shown in Fig. 5 can be modified to operate it as an induction generator at variable speed and the equations in a d-q model for stator and rotor sides are lined as follows.

Fig. 4
figure 4

Integration of DFIG with wind turbine

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Fig. 5
figure 5

The control scheme for MSC

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The stator and rotor circuit equations (referred to stator) in the stationary frame of reference become:

$${\mathrm{V}}_{\mathrm{s}}^{\mathrm{s}}={\mathrm{R}}_{\mathrm{s}}{\mathrm{i}}_{\mathrm{s}}^{\mathrm{s}}+\frac{\mathrm{d}{\uppsi }_{\mathrm{s}}^{\mathrm{s}}}{\mathrm{dt}},$$
(9)
$${\mathrm{V}}_{\mathrm{r}}^{\mathrm{s}}={\mathrm{R}}_{\mathrm{r}}{\mathrm{i}}_{\mathrm{r}}^{\mathrm{s}}+\frac{\mathrm{d}{\uppsi }_{\mathrm{r}}^{\mathrm{s}}}{\mathrm{dt}}.$$
(10)

The d-q transformed stator circuit equations in a synchronously rotating frame of reference are:

$${V}_{qs}={R}_{s}{i}_{qs}+\frac{\mathrm{d}{\uppsi }_{qs}}{\mathrm{dt}}+{\omega }_{s}{\uppsi }_{qs},$$
(11)
$${V}_{ds}={R}_{s}{i}_{ds}+\frac{\mathrm{d}{\uppsi }_{ds}}{\mathrm{dt}}-{\omega }_{s}{\uppsi }_{ds}.$$
(12)

Similarly, rotor circuit equations turn out to be:

$${V}_{qr}={R}_{s}{i}_{qr}+\frac{\mathrm{d}{\uppsi }_{qr}}{\mathrm{dt}}+({\omega }_{s}-{\omega }_{r}){\uppsi }_{qr},$$
(13)
$${V}_{dr}={R}_{s}{i}_{dr}+\frac{\mathrm{d}{\uppsi }_{dr}}{\mathrm{dt}}-{(\omega }_{s}-{\omega }_{r)}{\uppsi }_{dr}.$$
(14)

Flux linkages in terms of currents are given by:

$${\uppsi }_{qs}={L}_{s}{i}_{qs}+{L}_{m}{i}_{qr}= {L}_{Is}{i}_{qs}+{L}_{m}\left({i}_{qs}+{i}_{qr}\right),$$
(15)
$${\uppsi }_{ds}={L}_{s}{i}_{ds}+{L}_{m}{i}_{dr}={L}_{Is}{i}_{ds}+{L}_{m}\left({i}_{ds}+{i}_{dr}\right),$$
(16)
$${\uppsi }_{qr}={L}_{r}{i}_{qr}+{L}_{m}{i}_{qs}= {L}_{Ir}{i}_{qr}+{L}_{m}\left({i}_{qs}+{i}_{qr}\right),$$
(17)
$${\psi}_dr=L_r i_dr+L_m i_ds=L_Ir i_dr+L_m (i_ds+i_dr )$$
(18)
$${\uppsi }_{qm}={L}_{m}\left({i}_{qs}+{i}_{qr}\right),$$
(19)
$${\uppsi }_{dm}={L}_{m}\left({i}_{ds}+{i}_{dr}\right).$$
(20)

The electromechanical torque is given by

$${\mathrm{T}}_{e}=\left(\frac{3}{2}\right)\left(\frac{P}{2}\right)\left({\uppsi }_{ds}{i}_{qs}-{\uppsi }_{qs}{i}_{ds}\right),$$
(21)

where (P) is the number of poles of the induction machine.

$$\frac{d\left({w}_{r}/{w}_{b}\right)}{dt}=\frac{1}{2H}\left({\mathrm{T}}_{e}-{\mathrm{T}}_{m}\right),$$
(22)

where (H) is the inertia constant \(({w}_{b})\) is the base frequency and Tm is the machine induced torque. In order to make it work as a generator rotor is rotated using a wind turbine, this creates a reverse torque, and the power of the generator increase. Since there is a limitation because of a lack of field excitation, reactive power is supplied by connecting reactive load like a capacitor at the stator side.

3 Converter Modeling

The basic structure of DFIG consists of only two main controllers which are employed in Grid Side Converter (GSC) and Machine Side Converter (MSC). The GSC controller controls the DC link voltage and power exchange with the grid while the MSC controller controls the power of the stator. A classical vector control method is used in this work to control the DFIG [17]. DC link voltage is estimated by using the following equation [18, 19].

$${\mathbf{V}}_{\mathbf{D}\mathbf{C}}\ge \frac{2\sqrt{2}}{\sqrt{3}\mathbf{m}}{\mathbf{V}}_{\mathbf{a}\mathbf{b}}.$$
(23)

4 Machine Side Converter (MSC)

The MSC is designed by a vector control method using the stator flux scheme shown in Fig. 5. The d-axis is in alignment with the stator flux. There’s a linear relationship between stator flux and grid voltage. If we neglect the small voltage drop caused by stator resistance, we get:

$${V}_{qs}={V}_{g}\approx {\omega }_{s}{\psi }_{s}.$$
(24)

This results in the following equations

$${{\varvec{\uppsi}}}_{{\varvec{q}}{\varvec{s}}}={{\varvec{L}}}_{{\varvec{s}}}{{\varvec{i}}}_{{\varvec{q}}{\varvec{s}}}+{{\varvec{L}}}_{{\varvec{m}}}{{\varvec{i}}}_{{\varvec{q}}{\varvec{r}}}=0,$$
(25)
$${{\varvec{\uppsi}}}_{{\varvec{d}}{\varvec{s}}}={{\varvec{L}}}_{{\varvec{s}}}{{\varvec{i}}}_{{\varvec{d}}{\varvec{s}}}+{{\varvec{L}}}_{{\varvec{m}}}{{\varvec{i}}}_{{\varvec{d}}{\varvec{r}}}={{\varvec{\uppsi}}}_{{\varvec{s}}}.$$
(26)

From the above equations, we can calculate the d-q axis stator currents

$${\mathrm{i}}_{\mathrm{qs}}=-{\frac{{\mathrm{L}}_{\mathrm{m}}}{\mathrm{L}}}_{\mathrm{s }}{\mathrm{i}}_{\mathrm{qr}},$$
(27)
$${i}_{ds}=\frac{{\uppsi }_{s}-{L}_{m}}{{L}_{s}}{i}_{dr}.$$
(28)

Substituting the values of iqs and ids in Ps and Qs, we get

$${i}_{qr}=-{\frac{{2L}_{s}}{3{V}_{g}{L}_{s}}}{P}_{s},$$
(29)
$${i}_{dr}=-\frac{2{\mathrm{Q}}_{s}{L}_{m}}{3{V}_{g}{L}_{s}}{Q}_{s}.$$
(30)

The above-mentioned rotor dynamic and quadrature currents serve as a current controlling model of IG.

The PWM converter is employed on the rotor and the control is done by PWM signals, the stator and rotor current, and the position of the rotor [20].

The MSC converter controller can be designed using stator flux control. There are two cascaded control loops of the MSC control scheme. The d-axis and q-axis rotor current components are regulated independently by the inner current control loop with respect to some synchronously rotating reference frames [17].

The inner current control loop can be designed using the Eqs. (12) and (13). A Proportional and Integral (PI) controller is designed for this purpose. The proportional and integral gain is decided using these equations.

$${{\varvec{v}}}_{{\varvec{d}}{\varvec{r}}}={({\varvec{k}}}_{{\varvec{p}}}+\frac{{{\varvec{k}}}_{{\varvec{i}}}}{{\varvec{s}}})\left({{\varvec{i}}}_{{\varvec{d}}{\varvec{r}}}^{\boldsymbol{*}}-{{\varvec{i}}}_{{\varvec{d}}{\varvec{r}}}\right)-{\varvec{s}}{{\varvec{\omega}}}_{{\varvec{r}}}{\varvec{\sigma}}{{\varvec{L}}}_{{\varvec{r}}}{{\varvec{i}}}_{{\varvec{q}}{\varvec{r}}},$$
(31)
$${{\varvec{v}}}_{{\varvec{q}}{\varvec{r}}}={({\varvec{k}}}_{{\varvec{p}}}+\frac{{{\varvec{k}}}_{{\varvec{i}}}}{{\varvec{s}}})\left({{\varvec{i}}}_{{\varvec{q}}{\varvec{r}}}^{\boldsymbol{*}}-{{\varvec{i}}}_{{\varvec{q}}{\varvec{r}}}\right)+{\varvec{s}}{{\varvec{\omega}}}_{{\varvec{r}}}({\varvec{\sigma}}{{\varvec{L}}}_{{\varvec{r}}}{{\varvec{i}}}_{{\varvec{d}}{\varvec{r}}})+\frac{{{{\varvec{L}}}_{{\varvec{m}}}}^{2}}{{{\varvec{L}}}_{{\varvec{s}}}}{{\varvec{i}}}_{{\varvec{m}}{\varvec{s}}},$$
(32)

where σ is given by

$${\varvec{\sigma}}=1-\frac{{{{\varvec{L}}}_{{\varvec{m}}}}^{2}}{{{\varvec{L}}}_{{\varvec{s}}}\boldsymbol{ }{{\varvec{L}}}_{{\varvec{r}}}}.$$
(32)

The gains of the PI controller have been tuned using Ziegler Nichols method [21] followed by experimental fine tuning and are mentioned in Table 1.

Table 1 Parameters for PI controller
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5 Grid Side Converter (GSC)

The power of the grid is used to model the current loops that control the IGBTs using PI controllers. The active power components give the reference grid current of the dynamic axis, while the reactive power gives the grid current of the quadrature axis as in Eq. (33) to (36). The required vector control strategy is accomplished by aligning the dynamic axis of the synchronous frame with the vector of grid voltage.

$${P}_{g}=\frac{3}{2}\left({V}_{dg}{i}_{dg}+{V}_{qg}{i}_{qg}\right)=\frac{3}{2}{V}_{dg}{i}_{dg},$$
(33)
$${Q}_{g}=\frac{3}{2}\left({V}_{qg}{i}_{dg}-{V}_{dg}{i}_{qg}\right)=-\frac{3}{2}{V}_{dg}{i}_{qg},$$
(34)
$${i}_{dg}^{*}=\frac{2{P}_{g}^{*}}{3{V}_{dg}},$$
(35)
$${i}_{qg}^{*}=-\frac{2{Q}_{g}^{*}}{3{V}_{dg}}.$$
(36)

The three-phase line voltage \(\left({V}_{abc}\right)\) and current \(\left({I}_{abc}\right)\) are used to estimate the stator fluxes. The rotating angle of the rotor is obtained from DFIG and then the a-b-c model is transformed into a d-q model where all the rotating currents are obtained using PI controllers. Finally, rotor d-q voltages are accomplished as stated in Eq. (31) and (32), these switching voltages are used to generate PWM signals that control switching of IGBTs as shown in Fig. 6

Fig. 6
figure 6

The vector control diagram of the GSC mode

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$${V}_{af}={R}_{f}{i}_{ag}+\frac{d{i}_{ag}}{dt}{L}_{f}+ {V}_{ag},$$
(37)
$${V}_{bf}={R}_{f}{i}_{bg}+\frac{d{i}_{bg}}{dt}{L}_{f}+ {V}_{bg},$$
(38)
$${V}_{cf}={R}_{f}{i}_{cg}+\frac{d{i}_{cg}}{dt}{L}_{f}+ {V}_{cg}.$$
(39)

6 Results and Discussions

This section completely illustrates the DFIG model implementation and its operation through simulation results. The model is developed to test under three conditions i.e. sub-synchronous speed, synchronous speed, and super synchronous speed. The reactive and active power impacts on rotor speeds by connecting capacitor is observed against grid and machine side converters through voltages.

For DFIG to work in super-synchronous mode, the rotor angular frequency is much higher as compared to the stator angular frequency. Initially the value of slip is assumed to be zero and the turbine supply two times of the p.u torque to the rotor and thus the positive torque induces the voltage across the stator. The torque induced by the machine is shown in Fig. 7. It can be clearly seen that the torque induced is positive. The induced stator and rotor voltages are shown in Fig. 8. The waveform of induced stator three phase voltage frequency is found to be less as compared to the frequency of rotor. This implies that power is fed to the grid side. This clearly illustrates that slip has become negative and the machine is acting as generator. The active and reactive power consumed by the stator and rotor are shown in Figs. 9 and 10. It is clear that rotor active power consumed is almost negligible and reactive power consumed is due to reactive element connected at stator side.

Fig. 7
figure 7

Torque induced by machine running in super synchronous model

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Fig. 8
figure 8

Three phase stator and rotor voltage induced in super synchronous model

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Fig. 9
figure 9

Stator active and reactive power during super synchronous model

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Fig. 10
figure 10

Rotor active and reactive power in super synchronous model

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In synchronous mode, the rotor and stator frequency becomes equalized and in this way, the slip approaches to zero. In this mode, no power is transferred to the grid side by the induction generator. In this way, the active component of the rotor becomes zero however, the reactive power of the rotor will exist due to the reactive element connected by the stator as shown in Figs. 11 and 12. The induced torque in Fig. 13 shows that the induction machine is baring the load and at this stage the power is not delived to the grid side and nor we can say that the machine is totally running in motoring mode. The three phase rotor and stator side voltages induced are shown in Fig. 14. The system is highly stable due to frequency synchronization.

Fig. 11
figure 11

Stator side active and reactive power running in synchronous mode

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Fig. 12
figure 12

Rotor side power consumed in synchronous mode

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Fig. 13
figure 13

Torque induced in synchronous mode

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Fig. 14
figure 14

Three phase statot and rotor voltage induced in synchronous model

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In the third condition, the double fed induction generator is made to run in sub synchronous mode. For this purpose, the stator frequency will be more than that of rotor frequency. In this way, the DFIG will run below the synchronous speed and the rotor will not be able to transfer power towards the grid. This will cause the slip to be lesser than one and greater than zero, now the power from the grid will be consumed by the rotor. The DFIG running lesser than synchronous speed draws power from the grid side towards the rotor and now the rotor consumes both active and reactive power from the grid side. The torque induced by the IG is shown in Fig. 15 and it can be clearly seen that motor is bearing a load and its torque will be positive, the three phase voltage induced waveforms of stator and rotor clearly indicate that the frequency of rotor is less than the stator side frequency as in Fig. 16. Since the power is consumed by the motor therefore, the both active and reactive power component will be cosumed by both rotor and stator winding as shown in Figs. 17 and 18.

Fig. 15
figure 15

Torque induced in sub-synchronous mode

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Fig. 16
figure 16

Thre phase stator and rotor voltage in sub-synchronous mode

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Fig. 17
figure 17

Stator side active and reactive power in sub-synchronous mode

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Fig. 18
figure 18

Rotor side active and reactive power in sub-synchronous mode

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The above simulation model was also tested by setting the testing bed in the lab and Labsoft was used to establish the wind farm emulator. The experimental setup prepared is shown in Fig. 19 The modern wind systems employ DFIG for variable wind speed control and ensure optimum energy transfer. The experimental setup consists of thirty-seven units and the list is presented in Table 2. The first test performed shows the dependency of mechanical rotating speed over the generated supply frequency. The statistical data in Table 3 shows that the DFIG behaved as the synchronous generator over the variable mechanical speed range with a wide range of frequencies. The next test performed reveals the influence of variable frequency rotor and the following conclusions were made (i) the stator frequency could be held constant by adjusting rotor frequency for certain mechanical delivered speed by the wind turbine. (ii) At constant speed the stator frequency can be varied via rotor frequency and (iii) Stator speed is the sum of rotor frequency and the frequency of mechanical rotating wind turbine. the results have been summarized in Table 4.

Fig. 19
figure 19

The experimental setup of Grid-connected DFIG

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Table 2 Equipment used to connect DFIG to Grid
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Table 3 Mechanical speed influence over DFIG in synchronous mode
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Table 4 Mechanical speed influence over DFIG in for variable rotor frequency (sub-synchronous mode)
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The results obtained from Tables 3 and 4 help to formulate a relationship to understand the impact of changing rotor frequency at a certain rotor current over the per phase stator voltage. The results presented in Table 5 help to conclude that by increasing the rotor frequency by just 10 Hz will increase the stator voltage at 50 Hz proportionally. Also by increasing the rotor current for the same rotor frequency will also increase the induced stator voltage per phase. The results for the influence of rotor current over stator voltage at different levels of rotor frequency have been summarized in Table 5.

Table 5 Stator voltage at different levels of rotor frequency for variable rotor current
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In order to control power through DFIG, its power is varied under sub-synchronous mode. This mode power required to excite the generator is received from the grid and in this mode power is fed to the DFIG. And the results have been demonstrated in Fig. 20 The power through generator can also be controlled by speed variation of generator. The results for speed variation of generator for fixed power supplied by IG at 400 W can be controlled and fed to grid side is shown in Fig. 21. The GSC power will steady rise due to large consumption of reactive power. Similarly, the power can be controlled in super synchronous mode for both which means that now the rotor frequency is higher than stator frequency, this means that power is being fed to the grid side through MSC and GSC. In this case the DFIG power is steadily raised and the reactivein power of GSC will steadily decrease. The experimental result has been shown in Fig. 22.

Fig. 20
figure 20

Power control by DFIG running in subsynchronous mode at variable power supplied by GSC

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Fig. 21
figure 21

Power control by DFIG running in subsynchronous mode at veriable speed

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Fig. 22
figure 22

Power fed to grid by DFIG in super synchronous mode

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7 Conclusion

This paper presented the implementation of an analytical model of DFIG connected with wind turbines and its integration with the grid using current control loops. The implemented mathematical model was tested under synchronous, subsynchronous and super synchronous mode and the results obtained were briefly discussed in the above section. The results revealed that when the rotor is rotating at an angular frequency lower than the stator angular frequency then the power is fed to the rotor from grid side and when the angular frequency of rotor is higher than the stator angular frequency, the power is fed to the grid from rotor side. The mathematical model was also tested under the lab integrating the DFIG model with the grid under the same conditions and the results thus obtained completely validated our model. Further tests have been performed to analyze the change of rotor current and frequency over stator induced voltage. It showed that under sub synchronous mode the reactive power from GSC continuously increases in negative. However, in super-synchronous mode, the reactive power of GSC becomes positive due to a decrease in reactive power. The lab experiment has also been validated by running DFIG at variable and fixed speed to show the variation of power transfer from the grid to DFIG and toward the grid.