Solar cell implicit equation parameter identification method based on particle swarm optimization algorithm

Abstract

The invention discloses a solar cell implicit equation parameter identification method based on a particle swarm optimization algorithm, and is used for solving the technical problem of low identification precision of the solar cell parameter identification method. The technical scheme can efficiently extract five parameters of a solar cell model through identification by a fitness function design method based on an equation to be identified by aiming at a characteristic that the solar cell model is an implicit equation. In an identification process, the linear simplification of an equivalent equation and the default of the small-range parameter change do need to be carried out, so that an identification process is more flexible, adaptive and robust, and the precision of an identification result is higher. Meanwhile, the method also can be used for solving the identification problem of other implicit equation parameters in addition to the solar cell model, and has certain universality.

Description

technical field [0001] The invention relates to a solar cell parameter identification method, in particular to a solar cell implicit equation parameter identification method based on a particle swarm optimization algorithm. Background technique [0002] The document "Solar Cell Parameter Identification Method Based on Maximum Power Point, Proceedings of the 31st China Control Conference, 2012" discloses a conventional parameter identification method based on factory data to determine the volt-ampere characteristic curve. This method is based on the maximum power tracking characteristics of solar cells in photovoltaic power generation, combined with the extreme value expression of the volt-ampere characteristic equation of silicon solar cells at the maximum power point, using the voltage of silicon solar cells at the maximum power point measured under different light and temperature and current to establish a closed equation set containing four model parameters, including pho...

AI Technical Summary

Problems solved by technology

[0003] In order to overcome the deficiency of low identification accuracy of existing solar cell parameter identification methods, the present invention provides a solar cell implicit equation parameter identification method based on particle swarm optimization algorithm

At the same time, the method of the present invention can also be used to solve other implicit equation parameter identification problems except the solar cell model, and has certain universality

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