Comparison of metaheuristic methods objective function

Photovoltaic Parameters Estimation Using Hybrid Flower Pollination with Clonal Selection Algorithm

Ahmed Kamal RYAD, Ahmed Mohamed ATALLAH, Abdelhaliem ZEKRY


Extracting the parameters of photovoltaic (PV) cell is a vital process to accurately simulate the behavior of the cell. Various techniques are used to extract these parameters such as iterative, and metaheuristic methods. Although metaheuristic methods require more test points on the PV module, through this paper the optimization function is chosen to accurately adjust the I-V curve of the PV module based on less number of test points yet still achieve higher accuracy. A modified hybrid flower pollination method with clonal selection algorithm is suggested to extract the PV parameters and is compared with various metaheuristic methods to estimate the PV parameters of the single diode model, the two-diode model. In addition, modeling the PV at various irradiance and temperature levels was performed. Results show an excellent curve fitting for I-V characteristics and more accurate results in estimating the unknown parameters of PV cell.  

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