**3. Control system**

#### **3.1 Conventional wind power control scheme**

Owing to the alterations in the timing measures of the mechanical and electrical gestures, the DFIM-centered wind power control system has a multiple-layer control arrangement, with unified sub-systems. At the uppermost developed control stage, a maximum power point tracking procedure is applied to compute the generator speed set-point Ω<sup>∗</sup> *<sup>m</sup>* to produce the DFIG target power set point T<sup>∗</sup> *em*. The other control stage oversees the turbine pitch control scheme. The third and final control stage standardizes the generator torque, the real and reactive power, and the DC linkage voltage. The key limitations of the traditional control approach are explained in [25]. In the fractional load control process, the PI controller does not permit calibration of the commutation between the energy intensification and the momentary load depreciation, and at the full load control stage, the pitch-controlled generator speed directive can source acute power variations. Therefore, this study emphasizes the generator controller utilizing an adaptable tracing, self-adjustable PI controller framework. The suggested control system is disintegrated into various sub-categories entailing the fréchet derivative, the proportional, integral, and the derivative control. The PID control variables, *Kp*, *Ki*, and *Kd* are observed as the adaptable interfaces among the above sub-categories to self-adjusting these variables.

A reference current calculation and current control loop are presented as shown in **Figure 4** [26] and both the reference reactive power *Qsref* and *Qgref* are usually set to zero and can be modified depending on the grid requirements. The DC link reference voltage has a fixed value while the reference torque is determined by the maximum power point tracking control system. The vectorial control system of a grid-integrated DFIM is very similar to the traditional vectorial control system of a

#### **Figure 4.**

*Reference values entered in DFIG back to back converter [26].*

squirrel cage machine. DFIM is controlled in a synchronously revolving *dq* orientation structure, with the *d* axis adapted to the rotor flux space vector locus. The direct current is therefore related to the rotor side magnetic flux linkage although the quadrature current is related to the electromagnetic torque. By regulating autonomously, the two current modules, a disintegrated control between the torque and the rotor excitation current is achieved. Likewise, in the vectorial control system of a DFIM, the *d* and *q* axis components of the rotor current are controlled.

## **3.2 Maximum power point control**

The most commonly used wind turbine control strategy is illustrated in **Figure 5**, and consists of four operation zones, this shows the wind speed as a function of the wind speed [27]. This resembles an operation at full load condition. Here, the

**Figure 5.** *The operation zones for power point tracking for wind turbine [27].*

*Simulation Analysis of DFIG Integrated Wind Turbine Control System DOI: http://dx.doi.org/10.5772/intechopen.103721*

mechanical power can be restricted moreover by changing the pitch or using torque control. Usually, the electromagnetic torque is retained at an insignificant value and regulates the pitch angle to retain the wind turbine at extreme speed to maintain power output at a higher than rated wind speed.

The maximum power deviation with the rotational speed of DFIM is pre-established for every individual wind turbine. Owing to the intermittent character of the wind, it is vital to comprise a control unit to be able to follow maximum peak irrespective of the wind speediness. Due to the adaptive tracking and self-tuning capabilities, the two best MPC control methods are described in [27] as indirect speed control and direct speed control. The direct speed controller (DSC) as shown in **Figure 6** follow the maximum power curve more narrowly with rapid dynamics. Observing the description of the tip speed ratio, the optimum VSWT rotating speed *Ωtopt* may be established from the wind speed *Vw*, whereas *Tem* is the turbine electromagnetic torque, Ω*<sup>m</sup>* is rotating speed, *Tt*\_*est* is assessed turbine aerodynamics torque, and *P*max is the maximum powering point.

$$
\Omega\_m^\* = N \sqrt{\frac{T\_{t\_{-\text{eff}}}}{k\_{opt\\_t}}} \tag{29}
$$

$$P\_{\text{max}} = \frac{1}{2}\rho \quad \text{ $\pi$ } \text{  $R^5$  } \frac{\left(C\_{p\_-\text{max}}\right)}{\left(\lambda\_{opt}^3\right)} \left(\Omega\_m^\*\right)^3\tag{30}$$

$$P\_{\rm MPPT} = K\_{\rm opt} (\Omega^\* \, \_m)^3 \tag{31}$$

**Figure 6.** *Direct speed control [27].*

#### **3.3 Rotor side control**

The DFIG rotor variable's orientation must follow the orientation of the selected orientation parameter. Here, two algorithms are implemented, stator side voltage aligned control and stator side flux aligned control. Once this parameter vector is computed in the rotor side orientation structure, its comparative angle ð Þ*δ* to the rotor side orientation structure is designed and the rotor parameters are altered into the novel control-reference structure, as shown in **Figure 7** [21].

Vector control is applied to the rotor side converter to control the stator's active and reactive power. The direct axis loop is used to control reactive power whereas the quadrature axis is for active power control. The rotor converter obtains evaluations of rotor circuit parameters and is accountable for handling the reactive power flow between the stator and the power grid as well as regulating the generator torque. Its input parameters are not associated with the stator orientation structure. Though, it is exactly the stator target that must be measured and controlled. For the RSC to calculate an output stable with the stator's parameters, the rotor parameters articulated in the rotor d-q orientation structure must be revolved to be oriented with the control orientation structure. The RSC controller MATLAB block diagram is shown in **Figure 8**.

**Figure 7.** *Reference frames used in park transform [21].*

**Figure 8.** *RSC controller MATLAB block diagram.*

*Simulation Analysis of DFIG Integrated Wind Turbine Control System DOI: http://dx.doi.org/10.5772/intechopen.103721*

The equations used in the orientation process are [21]:

$$\mathcal{S}\_{r-d} = \mathcal{S}\_{r-q}' \sin\left(\delta\right) + \mathcal{S}\_{r-d}' \cos\left(\delta\right) \tag{32}$$

$$\mathcal{S}\_{r\ \ q} = \mathcal{S}\_{r\ \ q}' \cos\left(\delta\right) - \mathcal{S}\_{r\ \ d}' \sin\left(\delta\right) \tag{33}$$

Where:


#### **3.4 Grid side control**

The main objective of the grid side converter control model with ideal bidirectional switches as shown in **Figure 9** is to focus on the active and reactive powers delivered to the grid, keeping a constant DC-link voltage independent of the value and direction of the rotor power flow, and grid synchronization control. The grid side of the wind turbine system is composed of the grid side converter, the grid side filter, and the grid voltage. It converts voltage and currents from DC to AC, while the exchange of power can be in both directions from AC to DC (rectifier mode) and from DC to AC (inverter mode). The *d* � *q* axis voltage *Vgd* and *Vgq* of the grid side converter from the original three phases *Vga*, *Vgb*, *Vgc* is as below [27]:

$$V\_{\text{g}\cdot d} = V\_{\text{g}\cdot d} + R\_{\text{g}}I\_{\text{g}\cdot d} + L\_{\text{g}}\frac{dI\_{\text{g}\cdot d}}{dt} - \alpha\_{\text{s}}L\_{\text{g}}I\_{\text{g}\cdot q} \tag{34}$$

$$V\_{\text{g}\ \text{q}} = V\_{\text{g}\ \text{q}} + R\_{\text{g}}I\_{\text{g}\ \text{q}} + L\_{\text{g}}\frac{dI\_{\text{g}\ \text{q}}}{dt} + o\_{\text{t}}L\_{\text{g}}I\_{\text{g}\ \text{d}}\tag{35}$$

**Figure 9.** *Simplified converter, filter, and grid model [27].*
