Firefly Algorithm and Particle Swarm Optimization for photovoltaic parameters identification based on single model
Abstract
In this study, solar cell parameters, the most basic material of solar energy that has become increasingly widespread in recent years, are determined by Particle Swarm Optimization and Firefly and algorithms. The previously proposed single-diode solar cell model was used as a base for solar cells used in series connection and then in parallel connection with each other. Integral Absolute Error (IAE) was chosen as error criterion in heuristic algorithm for the parameters of a single diode solar cell. With this work, the parameters of the solar cell are brought closer to the reality, which is important because it will change the maximum power and efficiency to be drawn from the panes by designing a more accurate controller. In this study, it has been seen that the firefly algorithm gives more successful results when firefly and particle swarm optimization algorithms compared to the previous studies.