[PDF][PDF] Central composite design (CCD) for parameters optimization of maximum power point tracking (MPPT) by response surface methodology (RSM)

YK Yung, HS Chua, MJK Bashir… - Journal of Mechanics …, 2019 - researchgate.net
Journal of Mechanics of Continua and Mathematical Sciences, 2019researchgate.net
This paper focus on the CCD with RSM optimization of parameters. Design of Experiment
(DoE) hardware was developed with P&O MPPT algorithm to measure Input A: Input Voltage
(VIN), Input B: Input Current (IIN), Input C: Duty Cycle, Input D: Irradiance and output power.
The optimization of process parameters was successfully identified from the experimental
design and CCD results. The coefficient of determination of R2 is shown 99.89% which is a
good fit in the model. The adequacy prevision of 89.437 indicated an adequate signal and …
Abstract
This paper focus on the CCD with RSM optimization of parameters. Design of Experiment (DoE) hardware was developed with P&O MPPT algorithm to measure Input A: Input Voltage (VIN), Input B: Input Current (IIN), Input C: Duty Cycle, Input D: Irradiance and output power. The optimization of process parameters was successfully identified from the experimental design and CCD results. The coefficient of determination of R2 is shown 99.89% which is a good fit in the model. The adequacy prevision of 89.437 indicated an adequate signal and noise was negligible. The optimization of a set of experimental parameters and observed results were VIN: 18.82 V, IIN: 0.65 A, Duty Cycle: 85% and Irradiance: 883.79 W/m2. Overall, we concluded that input voltage is the most significant term influencing output power, following by input current, duty cycle and irradiance. All results were validated by experiments, simulations and theory calculation. The validation error results between predicted and experimental output power were shown that a maximum error at+ 3.65% and a minimum error at 0.00%, which had validated the accuracy of the prediction.
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