Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach

Abstract

Maximum power point of solar cells can be extracted by knowing the values of the electrical parameters. The validity of the obtained result depends on the accuracy of the model parameters. Hence, it is important to use a superior optimization technique to identify the optimal values of the parameters. Recently, a metaheuristic optimization algorithm, bird mating optimizer (BMO), has been devised which tries to metaphorically imitate the mating strategies of bird species. BMO employs several searching patterns to explore the region under consideration. This ability helps the algorithm to maintain the diversity and avoid premature convergence, and therefore, get close to the global solution. In this paper, the electrical parameters of a 57mm diameter commercial (RTC France) silicon solar cell are identified using BMO. The optimal parameters are then used to extract the maximum power point of the system. The accuracy of the proposed parameter identification approach is compared with the results found by the other optimization techniques. Simulation results accentuate the superior potential of BMO algorithm.