Photovoltaic cell parameter identification method based on improved particle swarm algorithm

A technology for improving particle swarms and photovoltaic cells. It is used in electrical digital data processing, calculation, and calculation models. It can solve problems such as poor convergence accuracy, slow convergence speed, and inability to overcome genetic algorithms that are prone to fall into prematurity. Easy to test and converge Fast speed, good effect of global optimization ability

Inactive Publication Date: 2016-12-07
STATE GRID QINGHAI ELECTRIC POWER +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, some scholars proposed to apply the genetic algorithm to the field of photovoltaic cell parameter identification. Under the premise of ensuring the identification accuracy, multiple sets of results obtained after photovoltaic cell parameter identification are converged into a set of parameter values. The advantage is that the error can be reduced by iteration. , so as to obtain the optimal estimated value of the parameters; and using the minimum gradient search method in the traditional genetic algorithm, an improved fusion genetic algorithm is formed, which can improve the accuracy and speed of parameter identification, but it still cannot overcome the genetic algorithm's tendency to fall into

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  • Photovoltaic cell parameter identification method based on improved particle swarm algorithm
  • Photovoltaic cell parameter identification method based on improved particle swarm algorithm
  • Photovoltaic cell parameter identification method based on improved particle swarm algorithm

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Embodiment 1

[0038] Embodiment 1. An m×n type photovoltaic module array in a photovoltaic grid-connected power generation system.

[0039] See attached Figure 1-A , the photovoltaic cell that constitutes the photovoltaic module is actually a large-area planar diode, and its work can be described by the equivalent circuit of a single diode in Figure 1; in the figure R L is the external load of the photovoltaic cell, and the output voltage of the photovoltaic cell is U L , the output current is I L .

[0040] See attached Figure 1-B , arrange a certain number of photovoltaic modules in series and parallel on a fixed support to obtain a photovoltaic array; assuming that the photovoltaic modules that constitute the photovoltaic array have ideal consistency, there are m series modules and n parallel modules, that is, photovoltaic parallel A series-parallel m×n type photovoltaic module array in a grid power generation system.

Embodiment 2

[0041] Embodiment 2, the implementation flow framework of the present invention.

[0042] See attached figure 2 , this embodiment gives the process framework of the recursive least squares photovoltaic cell parameter identification method with forgetting factor: establish the recursive least squares model form of the photovoltaic cell and determine the parameters to be identified→initialize the position and velocity of the particle swarm→calculate Particle fitness value, individual extremum, group extremum → update particle position and velocity → add Gaussian operator to individual extremum → calculate fitness value and update individual extremum → calculate the distance between each particle and the global extremum, if the distance If it is less than the threshold, the particle crosses the global extremum and the solution of the particle becomes the solution after crossing. If the distance is not less than the threshold, the solution of the particle is retained → then calcu...

Embodiment 3

[0043] Embodiment 3, specific implementation steps of the present invention.

[0044] Referring to accompanying drawings 1-2, the photovoltaic cell parameter identification method based on the improved particle swarm optimization algorithm includes the following implementation steps:

[0045] Step 1: Establish the photovoltaic cell I-V characteristic equation shown in the following formula, and determine the parameters to be identified; Among them, U L and I L are the output voltage and output current of the photovoltaic module, respectively, I sc is the photogenerated current, I 0 is the saturation current of the photovoltaic module when there is no light, R s is the series resistance of the photovoltaic module, R sh is the bypass leakage resistance of the photovoltaic module, q is the electronic charge, A is the constant factor, K is the Boltzmann constant, T is the absolute temperature value of the photovoltaic module under certain working conditions; determine the pa...

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Abstract

The invention discloses a photovoltaic cell parameter identification method based on an improved particle swarm algorithm. The implementation process framework of the method comprises the steps of establishing a recursive least-square model form of a photovoltaic cell and determining a parameter to be identified, initializing the position and speed of a particle swarm, calculating a particle fitness value, an individual extremum and a group extremum, updating the position and speed of particles, adding the individual extremum to a Gauss operator, calculating the fitness value and updating the individual extremum, calculating the distance between each particle and a global extremum, calculating the particle fitness value, conducting individual extremum and group extremum updating and outputting the optimal value of the photovoltaic cell parameter to be determined. The photovoltaic cell parameter identification method based on the improved particle swarm algorithm is used for parameter analysis of a series-parallel connection m*n type photovoltaic module array in a grid-connected photovoltaic power generation system and can be used for identifying an undetermined parameter of an I-V equation of the photovoltaic cell, determining an I-V mathematical model of the photovoltaic cell and analyzing failure activating causes of the photovoltaic cell.

Description

technical field [0001] The invention relates to the technical field of photovoltaic power generation, in particular to a method for identifying photovoltaic cell parameters in a photovoltaic grid-connected power generation system. Background technique [0002] The utilization of solar energy and the research on the characteristics of photovoltaic cells have become hot spots. With the deepening of research, scholars at home and abroad have proposed different photovoltaic cell models to describe the I-V curve. The I-V curve is a macroscopic expression of the characteristics of photovoltaic cells, and the parameters in it reflect the intrinsic characteristics of the model. By identifying the photovoltaic cell parameters, not only can the I-V equation be determined, and the output power of the photovoltaic array can be predicted by using the obtained I-V equation; and the cause of the photovoltaic cell failure can be further studied by analyzing the changes of these parameters. ...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06N3/00
CPCG06N3/006G16Z99/00
Inventor 杨立滨徐岩靳伟佳
Owner STATE GRID QINGHAI ELECTRIC POWER
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