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Photovoltaic cell model parameter identification method and device based on salp swarm algorithm

A photovoltaic cell model and salp group technology, which is applied in the field of photovoltaic cell model parameter identification method and device based on the salp group algorithm, can solve the problem of low matching degree of output characteristics, inaccurate parameter identification, and inaccurate photovoltaic cell equivalent model. Accuracy and other issues to achieve the effect of easy implementation, high flexibility, and improved accuracy

Inactive Publication Date: 2021-06-25
国网新疆电力有限公司信息通信公司 +5
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Problems solved by technology

[0004] The present invention provides a photovoltaic cell model parameter identification method and device based on the salp group algorithm, which overcomes the above-mentioned deficiencies in the prior art, and can effectively solve the problem of using a single diode model for equivalent completion of photovoltaic cell model parameter identification. The matching degree between the output characteristics of the photovoltaic cell and the single exponential function curve is not high, resulting in the inaccurate equivalent model of the output photovoltaic cell and inaccurate parameter identification

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  • Photovoltaic cell model parameter identification method and device based on salp swarm algorithm

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Embodiment 1

[0038] Embodiment 1: as attached figure 1 As shown, this embodiment discloses a photovoltaic cell model parameter identification method based on the salp group algorithm, including:

[0039] Step S101, obtaining output responses of photovoltaic cells under different light intensities, wherein the output responses include voltage, current and power;

[0040] Step S102, combining the double-diode equivalent circuit model, constructing the fitness function of the salp swarm algorithm;

[0041] Step S103, initializing the position of the salp group individual and setting the parameters of the salp group, wherein the parameters of the salp group include the population size of the salp group, the number of iterations, the upper and lower boundaries of the search space, leaders, followers and food sources;

[0042] Step S104, iterating in a loop, updating the positions of the leader and the follower, and outputting the identification result according to the set iteration end conditi...

Embodiment 2

[0047] Embodiment 2: as attached figure 2 As shown, this embodiment discloses a photovoltaic cell model parameter identification method based on the salp group algorithm, including:

[0048] Step S201, obtaining output responses of photovoltaic cells under different light intensities, wherein the output responses include voltage, current and power;

[0049] Step S202, obtaining the mathematical expression of the double-diode equivalent circuit model, that is, using the double-diode equivalent circuit model as the photovoltaic cell equivalent circuit model, as follows:

[0050]

[0051] in, V is the voltage across the load, I is the current through the load; I ph is the photogenerated current, I sd1 is the reverse saturation current of the first diode, Isd2 is the reverse saturation current of the second diode, η 1 , η 2 are the quality factor of the first diode and the quality factor of the second diode, respectively, R sh is the parallel resistance of the battery, ...

Embodiment 3

[0057] Embodiment 3: as attached image 3 As shown, this embodiment discloses a photovoltaic cell model parameter identification method based on the salp group algorithm, including:

[0058] Step S301, obtaining output responses of photovoltaic cells under different light intensities, wherein the output responses include voltage, current and power;

[0059] Step S302, combining the double-diode equivalent circuit model, constructing the fitness function of the salp swarm algorithm:

[0060] Step S303, setting the parameters of the salp group, the parameters of the salp group include the population size of the salp group, the number of iterations, the upper and lower boundaries of the search space, the leader, the followers and the food source, where the initial food source position is the one with the best fitness the location corresponding to the individual;

[0061] Step S304, randomly initialize the position of the individual in the salp group, and obtain the fitness of e...

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Abstract

The invention relates to the technical field of photovoltaic cells, in particular to a photovoltaic cell model parameter identification method and device based on the salp swarm algorithm. The method comprises the following steps: acquiring the output response of a photovoltaic cell under different illumination intensities; constructing a fitness function of the salp swarm algorithm in combination with a dual-diode equivalent circuit model; initializing the positions of salp swarm individuals and setting salp swarm parameters; and performing loop iteration, and outputting an identification result. According to the invention, the double-diode model is introduced as the equivalent circuit model of the photovoltaic cell, and parameter identification is carried out on the double-diode model through the salp swarm algorithm, so parameter identification is more in line with the actual situation compared with a single-diode model, and a matching degree with the output characteristics of the photovoltaic cell is higher; and meanwhile, parameter identification is carried out on the double-diode model by using the salp swarm algorithm, and the salp swarm algorithm is high in flexibility, easy to implement and not prone to falling into local optimum, so a global optimum point can be accurately searched, and parameter identification precision is effectively improved.

Description

technical field [0001] The invention relates to the technical field of photovoltaic cells, and relates to a photovoltaic cell model parameter identification method and device based on a salp group algorithm. Background technique [0002] Light energy is a renewable energy that focuses on ecological balance and promotes sustainable development. Due to a series of problems such as energy crisis, fuel depletion, environmental pollution caused by traditional energy sources and climate change, photovoltaic systems are becoming one of the most popular renewable energy technologies. However, before installing a photovoltaic system, its performance needs to be predicted for maximum power tracking, which in turn depends on the estimation of equivalent circuit parameters. At the same time, the change of equivalent circuit parameters can reflect the degradation state of photovoltaic cells. Therefore, the identification of photovoltaic cell model parameters is of great significance fo...

Claims

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Application Information

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IPC IPC(8): H02S50/10G06N3/00
CPCH02S50/10G06N3/006Y02E10/50
Inventor 周文婷黄辉王鑫李春龙胡长悦张海波刘杰马冲肖晗李庆艾科热木·艾则孜邓辉曾鹏飞柴谦益刘主光
Owner 国网新疆电力有限公司信息通信公司
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