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Photovoltaic (PV) is a renewable energy source that gain popularity in the past decades. The PV converts irradiance from the sun into electricity. As an engineer, you have been asked to analyse and design a PV generation system shown in Figure 1. With the knowledge of scientific programming, you have to WRITE THE SCRIPT for each task together with comment that explain the code. M 30 PYAR DE Figure 1 1. 20 voltage and current from the PV module, V and I respectively, has been collected. The data sensitivity is 1 V (V, is stepped 1 V between each data). Nevertheless, the collected data is not enough to produce a good result to model the PV, as shown in Figure 2. Write a MATLAB script that improve the result by increasing the sensitivity of the data from 1 V to 0.001 V using Piecewise cubic Hermite interpolation. Care Produc MY Figure 2 SAMPLE 2. The power produce by the PV module, P, is calculated by multiplying I with V. The P, is plotted against V and the result is shown in Figure 3. Write the MATLAB script that plot the P-V on your own similar to Figure 3 using the improved data. SAMPH Figure 3
3. The particle swarm optimization (PSO) is a useful algorithm that can be used to determine the minimum or maximum value. In the PV application, PSO can be used to determine V, with the highest P, which by referring to Figure 3 is when Vis 31 V. In the simulation, this can be done by slowly increase the V₁ until all the P point is collected. Unfortunately, in practice, this takes too long to complete. The PSO will select only several V to determine the maximum P, which produce faster result. Based on the list of instruction below, draw the flowchart and write the psedocode for the PSO used in the PV application. For further explanation, go to a. Load the data from Excel file. b. Initiate PSO i. Create variable dVpv (change of Vpv) that equal to zero. The dVpv is a horizontal vector with size of Npar (number of particle). Npar is equal to 5. ii. Create Vpv vector that start with 0 and end with 50 with size of Npar and evenly distribute (use linspace). iii. Find Ipv based on the Vpv using interpolated data. Calculate Ppv. iv. Find the best global Ppv and Vpv (Ppv_bg and Vpv_bg, respectively), which Ppv_bg is the highest value in Ppv and Vpv_bg is the corresponding to Ppv_bg. v. The best particle of Ppv and Vpv (Ppv_bp and Vpv_bp, respectively) is equal to Ppv and Vpv, respectively.
c. Iteration of PSO i. New dVpv is calculated using this formula: ii. New Vpv is calculated using this formula: iii. The Ipv and Ppy is calculated based on the new Vpv. Use the interpolation function. iv. Compare EACH value in Ppv with EACH Ppv_bp, separately. If the Ppv in the specific column is higher that the Ppy_bp of the same column, the Ppv_bp will be updated with the higher value. The Vpv bp of that specific column is updated with the Vpv of the same column. v. Compare EACH value in Ppv with Ppv_bg. If the Ppv in the specific column is higher that the Ppv_bg, the Ppv_bg will be updated with the higher value. The Vpv_bg is updated with the corresponding Vpv. vi. Repeat the step ci to cv 10 times d. Display the Ppv_bg and Vpv_bg. The variables are the location of the maximum power produce by the PV module. 4. Based on the flowchart or psudocode, write the MATLAB script for the PSO with this specific PV module. If the script is correctly written, the Ppv_bg and Vpv bg is around 89 and 30, respectively. Error of +1 is acceptable. 5. A sensor is needed to measure the Vpv for the use in PSO. The measured and the sense data is provided in Excel file. Using curve fitting, find the polynomial expression (2-degree fitting) to relate the measured and the sense voltage. Compare the polynomial expression with the data using figure. 6. To design the controller for the system, the transfer function for the power converter needs to be analysed. The transfer function for the power converter is: Write the MATLAB script that produce Figure 4. Samtale PH Figure 4
PV Data Vpv 050 0 5 6 7 10 11 13 16 18 20 22 30 36 42 43 44 47 48 50 Ipv 5 55 4.95 4.4 4 4 4 st 3.95 3.1 3 2.95 1 1 0.98 0.95 0.7 0.5 0.01 Sensor Data