## 5 Experimental Results and Discussion  
Experimentation is carried out to validate the performance of the proposed power management system and the pitch angle fluctuation controller. Algorithms and I/O data acquisition are implemented in Matlab/Simulink/QUARC. QUARC generates real-time code directly from the Simulink model and runs the generated code in real-time on the Windows target--all on the same PC. The Data Acquisition Board Q2 seamlessly interfaces with Simulink using Hardware-in-the-loop (HIL) blocks provided in the QUARC Targets Library [19]. The choice of the proportional gain \(K_{P}\) and integral gain \(K_{I}\) of the PI controller is determined by trial and error method, so that the controller is tuned to achieve good performance. The value of the error tolerance \(\varepsilon\) is 0.03 W. Theoretically, reducing the value of this parameter will improve the behavior of the controller. However, its choice depends on the performance of the PI controller in transient operation. The wind speed pattern is artificially and randomly generated by the blower motor. Initially, one bank must be turned ON in order to connect the generator to the load. Also, the banks can be manually turned ON/OFF by the supervisor before running the system. Then, the automatic switching will change the states of the banks depending on the generated power from the wind turbine and the bank's priority. Figure 6: Flow chart of the PI pitch fluctuation controller. The power reference is generated based on the state of the bank's switches, manually chosen by the supervisor and the available power from wind. The pitch angle controller adjusts the pitch angle in order for the generated power to track the reference one as shown in Figure 7. The banks are automatically switched ON/OFF, based on the Boolean expressions in (3) of the automatic switching system, as shown in Figure 8, where 1 \(\equiv\) ON and 0 \(\equiv\) OFF. The red dashed line represents the banks' switching states following the power reference, and the black line represents the automatic switching based on the actual power. It can be observed that the wind turbine starts to provide power after 8 s, due to its inertia, and the bank 2, turned ON by the supervisor, will automatically turn OFF, as the generated power did not reach the power reference before 8 s. In this application, where only four banks are used, the performances of the automatic switching system and the power tracking are good. However, the pitch angle is continuously changing and fluctuating around a constant value due to the power error, as shown in Figure 7.  
Figure 8: Automatic switching of the banks for the power reference of four banks (PI pitch angle controller). Figure 7: Generated power, reference power under PI pitch angle controller. The result of the modified PI pitch angle controller for the same application is shown in Figure 9, where the pitch angle is held constant during the power step, which reduces the activity of the pitch actuator. Less fluctuation in the power is observed during steady state operation compared to the result of the standard PI controller, which provides a consistent brilliance of the lights. However, some side effects occur in the automatic switching (Figure 10), as banks 2, 3 and 4 turn OFF during a short time of about 1\(\sim\)2 s, but not seen by the eye, due to undesirable changes in the power out of the error band and wind speed variation. In Figure 11, a new profile for the power reference, including the six banks, is provided to check the effectiveness of the proposed system for another scenario. It is observed that the power tracking is still good under the PI pitch angle controller. Due to the transition from one step to another, the power is  
Figure 10: Automatic switching of the banks for the power reference of four banks (modified PI pitch angle controller). Figure 9: Generated power, reference power under modified PI pitch angle controller.