Abstract
The design of a solar PV system and its performance evaluation is an important aspect before going for a mass-scale installation and integration with the grid. The parameter evaluation of a solar PV model helps in accurate modeling and consequently efficient designing of the system. The parameters appear in the mathematical equations of the solar PV cell. A Chaos Induced Coyote Algorithm (CICA) to obtain the parameters in a single, double, and three diode model of a mono-crystalline, polycrystalline, and a thin-film solar PV cell has been proposed in this work. The Chaos Induced Coyote Algorithm for extracting the parameters incorporates the advantages of the conventional Coyote Algorithm by employing only two control parameters, making it easier to include the unique strategy that balances the exploration and exploitation in the search space. A comparison of the Chaos Induced Coyote Algorithm with some recently proposed solar photovoltaic cell parameter extraction algorithms has been presented. Analysis shows superior curve fitting and lesser Root Mean Square Error with the Chaos Induced Coyote Algorithm compared to other algorithms in a practical solar photovoltaic cell.
Highlights
Renewable energy, from the sun, has increased in usage due to the increasing population, ever-growing industrial needs, depletion of fossil fuel reserves, and many environmental problems [1,2]
The results show that the Coyote Optimization Algorithm (COA) technique with chaos takes less time to converge with a lesser number of iterations
On comparing the results with various other parameter extraction techniques, it was observed that COA attains the best value of the objective function (RMSE) when used with chaotic functions
Summary
From the sun, has increased in usage due to the increasing population, ever-growing industrial needs, depletion of fossil fuel reserves, and many environmental problems [1,2]. The complexity and non-linearity of the solar cell equations, in addition to various instability problems, act as a hurdle to the PV system [4,5,6,7]. Several other reasons, including temperature, solar radiation, cable losses, dust accumulation, soiling, and shading, affect I–V characteristics [8,9]. It becomes necessary to develop accurate models for it. The literature proposes different models to represent a solar cell differently from each other by the number of diodes they incorporate. The models represent the current-voltage characteristics (I–V), but only for domestic purposes. A three diode model (TDM) [12] was developed, which can be used for industrial applications [13]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
