DETERMINACIÓN DE USOS

One of the issues in WPGS control is the measurement of the wind speed. The accuracy of the wind speeds measurement can not be ensured using sin- gle anemometer [36]. Also, the data recorded using SCADA system contain noticeable deviations which influence in the power conversion efficiency [113].

4.4 Simulation Results and Analysis 66

In this controller the wind speed is estimated using MPPT algorithm and the reference speed is generated using the estimated data. The wind power model which is expressed in equations (2.1.2) and (2.1.4) can be solved for the wind speed and the (Pm) is assumed to be the output DC power (V I). The estimated

wind speed can be shown as the following: Vw = −D21ω2r± p D2 21ωr4−4D11ωr(D31ω3r −V I) 2D11ωr . (4.3.24)

where D11 = 0.0960, D21 = −0.0098 and D31 = −0.0040. The MPPT con- troller is implemented in the proposed controller-II which is presented in 4.3.2.

4.4

Simulation Results and Analysis

The control diagrams of the two developed MPPT controllers, i.e. controller- I and controller-II are shown in Figs. 4.2 and 4.3 respectively. For both the controllers, the d-axis and q-axis models are obtained and the measurement of wind speed is required. The PMSG voltage and current are measured as well as the rotor position. Figure 4.4 shows the control block diagram of the third proposed controller which is controller-III.

In this research, the wind turbine is modelled as a VAWT unit and the generator is a PMSG. The WPGS model has been simulated under variable wind speeds. The wind speed function starts at 8 m/s then it goes to 10 m/s. The parameters of the PMSG and the VAWT employed in this simulation are illustrated in Table 3.1.

The three controllers have been simulated using MATLAB/SIMULINK. Figure 4.5 shows the speed dynamic boundary of the system. It is clear from the Figure 4.5a, that the speed boundary is decreasing when the PMSG is accelerating. In addition, the integration effect makes the boundary limits changing in a soft manner. It can be noted with the illustration of Figure 4.5b that during transients, the dynamic boundary converges smoothly and

4.4 Simulation Results and Analysis 67

Figure 4.2: The control diagram for controller-I

Figure 4.3: The control diagram for controller-II

fast enough to ensure the system robustness. High frequency oscillations are shown in the boundary limits. These oscillations are caused by the switching frequency since the boundary limit are affected by the error and the corrective

4.4 Simulation Results and Analysis 68

Figure 4.4: The control diagram for controller-III

actions. Figures 4.6 shows the actual speed tracking the reference speed for the first proposed controller (controller-I). It is noticeable that the actual speed accurately tracking the reference speed without any overshoots or steady-state errors. Also, the response speed is very fast and the settling time is at satis- factory level.

Figure 4.8 shows the actual speed tracking the reference speed for the second proposed controller (controller-II). It is noticeable that the actual speed is perfectly tracking the reference speed. There is a small overshoot appears in the speed response, which can be acceptable. The response speed is very fast and the settling time is at satisfactory level.

Figure 4.10 shows the actual speed tracking the reference speed for the third proposed controller (controller-III). Although, the speed response shows no overshoots. The raising time is slower than the previous two controllers. It is clear that the actual rotor speed is perfectly tracks the reference generated speed.

4.4 Simulation Results and Analysis 69

(a) The designed speed control boundary.

(b) A zoom in the designed speed control boundary.

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Figure 4.6: Actual speed tracking the reference speed for controller-I (i).

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Figure 4.8: Actual speed tracking the optimum speed for controller-II (ii).

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Figure 4.10: Actual speed tracking the reference speed for controller-III (iii).

4.4 Simulation Results and Analysis 73

Table 4.1: Comparison between Residue controllers-I, II and III.

Residue Residue Residue

controllers-I controllers-II controllers-III

Rise Time (ms) 52.5 70 60

Settling Time (ms) 210 300 450

Steady-States error (rad\s) 0.01 0.10 0.02

Power coefficient (Cp) 0.2221 0.2221 0.2221

The maximum conversion of power is ensured and clearly shown in Figs. 4.7 , 4.9 and 4.11. The Cp is at its maximum value of 0.22. The improvement

in the energy conversion ratio is significant as compared to results obtained in Chapters 3 and 2. The comparison between the three proposed residue controllers have been undertaken and pillustrated in Table 4.1.

The estimated wind speed algorithm has been implemented to residue controller-II. The reference rotation speed has been estimated using the value obtained from wind speed estimation algorithm. Figure 4.12 shows the actual rotor speed tracking the estimated reference speed generated from the MPPT algorithm. Also, the actual reference speed which is obtained from real wind measurement is shown in the figure. It is clearly shown that the estimated reference speed is almost equal to the actual reference speed. The TSR which is optimal at 0.82 can be shown in figure 4.14. Moreover, it is noticeable that the maximum power extraction is achieved and Cp is at its maximum value of

4.4 Simulation Results and Analysis 74

Figure 4.12: Actual speed tracking the estimated reference speed.