CN113033136B - Simplified photovoltaic cell physical parameter extraction optimization method and system - Google Patents

Simplified photovoltaic cell physical parameter extraction optimization method and system Download PDF

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CN113033136B
CN113033136B CN202110171948.3A CN202110171948A CN113033136B CN 113033136 B CN113033136 B CN 113033136B CN 202110171948 A CN202110171948 A CN 202110171948A CN 113033136 B CN113033136 B CN 113033136B
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张云鹏
郝鹏
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Abstract

The disclosure provides a simplified photovoltaic cell physical parameter extraction optimization method and system, comprising: obtaining a photovoltaic cell panel equivalent circuit model, and replacing all parameters containing reference conditions with unknown coefficients to obtain a first conversion equation; inputting short-circuit current, open-circuit voltage, maximum power point, first set value multiple point of open-circuit voltage and second set value multiple point of short-circuit current of I-V curve under different working conditions, and using the error of the input point as a target function to carry out optimization by using the target function; and inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters. The influence of the selection of the reference condition is eliminated. In addition, the whole solving process only needs one-time optimization, and the solving steps are greatly simplified.

Description

Simplified photovoltaic cell physical parameter extraction optimization method and system
Technical Field
The disclosure belongs to the technical field of photovoltaic cell parameter prediction, and particularly relates to a simplified photovoltaic cell physical parameter extraction optimization method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In recent years, with the increase of global energy problems, the photovoltaic power generation installation has increased greatly. The photovoltaic energy is used as renewable energy, has the advantages of cleanness, no pollution, reliability, safety, easy maintenance and the like, and has wide development prospect. Therefore, modeling of photovoltaic systems is critical to the design, manufacture, and prediction of photovoltaic systems.
On the basis of previous studies, many circuit models of photovoltaic panels have been proposed, and the single-diode model is most commonly used at present. It comprises a photo-generated current source, a diode and two equivalent resistors, and comprises five parameters with definite physical meanings. The model is widely applied to modeling of the photovoltaic cell due to simple structure and high precision.
Most current multi-condition modeling methods are based on model parameters under reference conditions, typically from photovoltaic manufacturers' data sheets. However, the photovoltaic panel usually works at different illumination temperatures, and therefore, the data under the reference condition is not enough to accurately predict the working characteristics of the photovoltaic panel. In addition, the numerical algorithm is the algorithm with the highest precision in the existing algorithms for solving the parameters, but the calculation speed is very low because of huge calculation amount.
Disclosure of Invention
In order to overcome the defects of the prior art, the method for extracting and optimizing the physical parameters of the photovoltaic cell is simplified, and influences caused by selection of reference conditions are eliminated.
In order to achieve the above object, one or more embodiments of the present disclosure provide the following technical solutions:
in a first aspect, a simplified photovoltaic cell physical parameter extraction optimization method is disclosed, comprising:
obtaining a photovoltaic cell panel equivalent circuit model, and replacing all parameters containing reference conditions with unknown coefficients to obtain a first conversion equation;
inputting short-circuit current, open-circuit voltage, maximum power point, first set value multiple point of the open-circuit voltage and second set value multiple point of the short-circuit current of the I-V curve under different working conditions, and optimizing by using the target function with the error of the input points as the target function;
and inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters.
In a further technical scheme, the equivalent circuit model of the photovoltaic cell panel can be a single-diode model,
in a further technical solution, the first conversion equation is:
Iph＝A·S+B·T-C
Figure BDA0002939218350000021
Rs＝E
Rsh＝F/S
n＝G
A-G is a constant and is suitable for any condition, the right side of the equation only contains illumination and temperature, and the data is applied to fit the first conversion equation, so that all the constants can be obtained.
In some embodiments, an average root mean square error is used
Figure BDA0002939218350000022
Optimizing as a target function;
Figure BDA0002939218350000023
wherein N ispRepresenting the number of points on all curves, NlRepresenting the number of all curves, N representing the number of points on each curve, I(j，i)And
Figure BDA0002939218350000024
respectively representing the measured current and the calculated current, by
Figure BDA0002939218350000025
To indicate the error between the calculated value and the measured value.
Preferably, the I-V curve can be described by a short circuit current point, an open circuit voltage point, a maximum power point, a multiple of the open circuit voltage and a multiple of the short circuit current.
According to a further technical scheme, the normalization processing is carried out on the multiple points used for describing the I-V curve.
Preferably, the error describing the doubling point of the I-V curve is taken as an objective function, the objective function being:
Figure BDA0002939218350000031
wherein Isc(i),Voc(i),Im(i),I0.6Isc(i)V0.Voc(i)Respectively representing the short-circuit current, the open-circuit voltage and the current of the maximum power point of the ith I-V actual measurement curve, the current with the current value of 0.6 time of the short-circuit current and the voltage with the voltage value of 0.6 time of the open-circuit voltage, and the subscript' open-circuit voltage represents the calculated value of the corresponding current or voltage.
In a second aspect, a system for optimizing multi-condition parameter prediction of operating characteristics of photovoltaic cells is disclosed, comprising:
the photovoltaic cell panel equivalent circuit model is obtained through a first conversion equation building module, all parameters containing reference conditions are replaced by unknown coefficients, and a first conversion equation is obtained;
the target function building module inputs short-circuit current, open-circuit voltage, maximum power point, first set value multiple point of open-circuit voltage and second set value multiple point of short-circuit current of the I-V curve under different working conditions, takes the error of the input points as a target function, and utilizes the target function to carry out optimization;
and inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters.
The above one or more technical solutions have the following beneficial effects:
the method comprises the steps of selecting a photovoltaic cell panel equivalent circuit model and a conversion equation model with corresponding parameters changing along with the illumination temperature, replacing all terms containing reference conditions with constants, inputting five special point information of I-V curves under different working conditions, and optimizing by taking errors of the five special point information as a target function to obtain a new conversion equation. The improved objective function greatly reduces the calculation time for fitting a large amount of data, and improves the efficiency of solving the working characteristics of the photovoltaic cell under any condition. The method is simple and easy to operate, can be easily realized through mathematical software programming, and can accurately and quickly predict the working characteristics of the photovoltaic cell panel at any illumination temperature.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
FIG. 1 is an equivalent circuit diagram of a single diode model according to the present disclosure;
fig. 2 is a flow chart of a method of an embodiment of the disclosure.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
Example one
The embodiment discloses a simplified photovoltaic cell physical parameter extraction optimization method, which specifically comprises the steps of fitting a large number of photovoltaic characteristic curves through an optimization algorithm, solving model coefficients under any working condition and further predicting photovoltaic cell physical parameters. The method avoids the problem that the traditional prediction method needs to set reference conditions, improves the objective function, greatly reduces the calculation time for fitting a large amount of data, and improves the efficiency of solving the working characteristics of the photovoltaic cell under any conditions.
The method comprises the steps of fitting a large number of five special working points on a photovoltaic characteristic curve at different illumination temperatures, solving to obtain model coefficients under any conditions, further obtaining physical parameters of the photovoltaic cell, calculating the working characteristics of the photovoltaic cell, and solving the problems of maximum power point tracking, power prediction and the like.
Regarding the five special operating points, firstly, the short-circuit current point, the open-circuit voltage point and the maximum power point determine the approximate shape of the whole I-V curve, and if the general three points are used for comparison, the whole curve is compared. In addition, the 0.6Voc point and the 0.6Isc point are used in some documents to find parameters and show better effects, and the two points are used for determining the specific shape of the whole I-V curve. The distribution of five points is relatively uniform for an I-V curve, and the condition that the error proportion is not uniform is avoided.
In an embodiment of the present disclosure, a simplified photovoltaic cell physical parameter extraction optimization method includes:
obtaining a photovoltaic cell panel equivalent circuit model, and replacing all parameters containing reference conditions with unknown coefficients to obtain a first conversion equation;
inputting short-circuit current, open-circuit voltage, maximum power point, first set value multiple point of open-circuit voltage and second set value multiple point of short-circuit current of I-V curve under different working conditions, and using the error of the input point as a target function to carry out optimization by using the target function;
and inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters.
The specific process of the invention is as follows: selecting a photovoltaic cell panel equivalent circuit model and a conversion equation model with corresponding parameters changing along with the illumination temperature, replacing all terms containing reference conditions with constants, then inputting five special point information of I-V curves under different working conditions, and optimizing by adopting a formula (13) as a target function to obtain a new conversion equation, namely a first conversion equation. The method is simple and easy to operate, can be easily realized through mathematical software programming, and can accurately and quickly predict the working characteristics of the photovoltaic cell panel at any illumination temperature. The general technical flow chart is shown in the attached figure 2.
The related technical scheme is described in detail as follows:
taking a single diode model as an example, an equivalent circuit diagram is shown in fig. 1. Applying kirchhoff's current law to obtain the I-V relation:
Figure BDA0002939218350000061
in the formula: vt＝KT/q；
Iph: generating a current; i is0: diode reverse saturation current; n: a diode ideality factor; rsh: a resistor is connected in parallel; rs: a series resistor; n is a radical ofs: the number of photovoltaic cells connected in series; v: outputting the voltage; i: outputting current; t: a photovoltaic cell temperature; k is 1.38006 x 10-23J/K；q＝1.60218×10-19C；
The conversion equation of the change of the physical parameters of the photovoltaic cell along with the illumination temperature is not yet determined, and only one form of conversion equation is given herein, including but not limited to one form:
Iph＝[Iph,ref+αIsc(T-Tref)]·S/Sref (2)
Figure BDA0002939218350000062
Rs＝Rs,ref (4)
Rsh＝Rsh,ref·Sref/S (5)
n＝nref (6)
wherein the subscripts denote the values of the respective parameters under their reference conditions, S denotes the intensity of the illumination, αIscRepresenting the temperature coefficient of the short circuit current. The five parameters under any working condition can be obtained by converting an equation after the parameters under the reference condition are obtained. The invention replaces all the parameters containing the reference condition with unknown coefficients, andthe following conversion equation is obtained:
Iph＝A·S+B·T-C (7)
Figure BDA0002939218350000063
Rs＝E (9)
Rsh＝F/S (10)
n＝G (11)
wherein A-G are constants, applicable to any condition. Therefore, the right side of the above formula only contains illumination and temperature, and all constants can be obtained by fitting a large number of I-V curves measured at different illumination temperatures. After such a transition, the influence of the reference condition is successfully eliminated.
However, this conversion brings about problems of many optimization parameters and large calculation amount. The current method generally adopts the mean root mean square error
Figure BDA0002939218350000071
The optimization is performed as an objective function, which is defined as:
Figure BDA0002939218350000072
wherein N ispRepresenting the number of points on all curves, NlRepresenting the number of all curves, N representing the number of points on each curve, I(j,i)And
Figure BDA0002939218350000073
representing the measured current and the calculated current, respectively. By using
Figure BDA0002939218350000074
To indicate the error between the calculated value and the measured value, with smaller values representing smaller errors. The objective function needs to calculate the current of all points to calculate the error, and has large calculation amount and high time cost. While only five distinct points are typically required to accurately describe an I-V curve. Thus, the deviceThe invention adopts the errors of five special points as the target function, thereby greatly reducing the calculation amount. The five special points are short-circuit currents (I)sc) Point, open circuit voltage (V)oc) Point, maximum power point (here maximum power point current I)mExpressed by (V), 0.6 times the open circuit voltage (0.6V)oc) 0.6 times (0.6I) of point and short-circuit currentsc) And (4) point. The above multiple may be considered to be set between 0.5 and 0.7, preferably 0.6, and since the voltage and current belong to different dimensions and are normalized for error addition, the new objective function is shown in equation (13):
Figure BDA0002939218350000081
wherein Isc(i),Voc(i),Im(i),I0.6Isc(i)V0.Voc(i)Respectively representing the short-circuit current, the open-circuit voltage and the current of the maximum power point of the ith I-V actual measurement curve, the current with the current value of 0.6 time of the short-circuit current and the voltage with the voltage value of 0.6 time of the open-circuit voltage, and the subscript' open-circuit voltage represents the calculated value of the corresponding current or voltage.
After normalization, the effect of each point on the result is the same and takes into account both the current and voltage effects. The simplified objective function can greatly reduce the calculation amount in the fitting process.
The embodiment of the disclosure is a novel simplified method for extracting physical parameters of a photovoltaic cell under multiple conditions, the step of obtaining the parameters under the reference condition is omitted, and the parameters under any condition are solved through one-step optimization. Compared with the traditional method for solving parameters under any condition by using a single condition, the method provided by the invention does not need to set a reference condition, is suitable for various photovoltaic cell equivalent circuit models and conversion equations, and adopts a large amount of I-V data under different working conditions to solve the parameters under any condition, so that the calculation result is more reasonable and accurate. In addition, the invention greatly improves the calculation efficiency through the simplified objective function.
Example two
It is an object of this embodiment to provide a computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the program.
EXAMPLE III
An object of the present embodiment is to provide a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
Example four
The purpose of this embodiment is to provide an optimization system for photovoltaic cell operating characteristic multi-condition parameter prediction, including:
the photovoltaic cell panel equivalent circuit model is obtained by a first conversion equation building module, all parameters containing reference conditions are replaced by unknown coefficients, and a first conversion equation is obtained;
the target function building module inputs the short-circuit current, the open-circuit voltage, the maximum power point, the first set value multiple point of the open-circuit voltage and the second set value multiple point of the short-circuit current of the I-V curve under different working conditions, takes the error of the input points as a target function and utilizes the target function to carry out optimization;
and inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters.
The optimization algorithm in the embodiment of the present disclosure may be selected from a particle swarm algorithm, a bee optimization algorithm, a suburb optimization algorithm, and the like, as long as the algorithm is capable of finding a set of parameters that can minimize the objective function value after the parameters that need to be optimized are given.
The steps involved in the apparatuses of the above second, third and fourth embodiments correspond to the first embodiment of the method, and the detailed description thereof can be found in the relevant description of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media containing one or more sets of instructions; it should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any of the methods of the present disclosure.
Those skilled in the art will appreciate that the modules or steps of the present disclosure described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code executable by computing means, whereby the modules or steps may be stored in memory means for execution by the computing means, or separately fabricated into individual integrated circuit modules, or multiple modules or steps thereof may be fabricated into a single integrated circuit module. The present disclosure is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.

Claims (7)

1. The simplified photovoltaic cell physical parameter extraction optimization method is characterized by comprising the following steps:
obtaining a photovoltaic cell panel equivalent circuit model, and replacing all parameters containing reference conditions with unknown coefficients to obtain a first conversion equation;
the first conversion equation is:
Iph＝A·S+B·T-C
Figure FDA0003589111690000011
Rs＝E
Rsh＝F/S
n＝G
A-G is a constant and is suitable for any condition, the right side of the equation only contains illumination and temperature, and the first conversion equation is fitted by using data, so that all constants can be obtained; i isph: generating a current; s represents the illumination intensity; i is0: diode reverse saturation current; rsh: a resistor is connected in parallel; rs: a series resistor; t: a photovoltaic cell temperature;
inputting short-circuit current, open-circuit voltage, maximum power point, first set value multiple point of open-circuit voltage and second set value multiple point of short-circuit current of I-V curve under different working conditions, and using the error of the input point as a target function to carry out optimization by using the target function;
using mean root mean square error
Figure FDA0003589111690000012
Optimizing as a target function;
Figure FDA0003589111690000013
wherein N ispRepresenting the number of points on all curves, NlRepresenting the number of all curves, N representing the number of points on each curve, I(j,i)And
Figure FDA0003589111690000014
respectively representing the measured current and the calculated current, by
Figure FDA0003589111690000015
To indicate the error between the calculated value and the measured value;
inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters;
five physical parameters being I in a single diode modelPh、I0、Rs、RShAnd n.
2. The simplified photovoltaic cell physical parameter extraction optimization method of claim 1, wherein the I-V curve is described by a short circuit current point, an open circuit voltage point, a maximum power point, a multiple of open circuit voltage and a multiple of short circuit current.
3. The simplified photovoltaic cell physical parameter extraction optimization method of claim 2, wherein the normalization process is performed on the multiple points used to describe the I-V curve.
4. The simplified photovoltaic cell physical parameter extraction optimization method of claim 2, wherein the error describing the multiple points of the I-V curve is taken as an objective function, the objective function being:
Figure FDA0003589111690000021
wherein Isc(i),Voc(i),Im(i),I0.6Isc(i)V0.6Voc(i)Respectively represent the short-circuit current, the open-circuit voltage, the current of the maximum power point, the current with the current value of 0.6 time of the short-circuit current and the voltage with the voltage value of 0.6 time of the open-circuit voltage of the ith I-V actual measurement curve, and the subscript 'cal' represents the calculated value of the corresponding current or voltage.
5. The optimization system for predicting the operating characteristics of the photovoltaic cell through multiple condition parameters is characterized by comprising the following steps:
the photovoltaic cell panel equivalent circuit model is obtained by a first conversion equation building module, all parameters containing reference conditions are replaced by unknown coefficients, and a first conversion equation is obtained;
the first conversion equation is:
Iph＝A·S+B·T-C
Figure FDA0003589111690000031
Rs＝E
Rsh＝F/S
n＝G
A-G is a constant and is suitable for any condition, the right side of the equation only contains illumination and temperature, and the first conversion equation is fitted by using data, so that all constants can be obtained; i isph: generating a current; s represents the illumination intensity; I.C. A0: diode reverse saturation current; rsh: a resistor is connected in parallel; rs: a series resistor; t: a photovoltaic cell temperature;
the target function building module inputs short-circuit current, open-circuit voltage, maximum power point, first set value multiple point of open-circuit voltage and second set value multiple point of short-circuit current of the I-V curve under different working conditions, takes the error of the input points as a target function, and utilizes the target function to carry out optimization;
using mean root mean square error
Figure FDA0003589111690000032
Optimizing as a target function;
Figure FDA0003589111690000033
wherein N ispRepresenting the number of points on all curves, NlRepresenting the number of all curves, N representing the number of points per curve, I(j,i)And
Figure FDA0003589111690000034
respectively representing the measured current and the calculated current, by
Figure FDA0003589111690000035
To represent the error between the calculated value and the measured value;
inputting the illumination temperature of the condition to be predicted to obtain the corresponding values of the five physical parameters;
five physical parameters are single diode mouldIn form IPh、I0、Rs、RShAnd n.
6. A computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method of any one of claims 1 to 4.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, is adapted to carry out the steps of the method according to any one of the preceding claims 1 to 4.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104778352A (en) * 2015-03-31 2015-07-15 国家电网公司 Seven-parameter photovoltaic cell output characteristic modeling method based on STFT (Short Time Fourier Transform) operator
CN106468935A (en) * 2016-09-18 2017-03-01 中州大学 A kind of segmented fitting seeks solaode peak power point methods
CN108365822A (en) * 2018-04-12 2018-08-03 山东大学 The prediction technique and system of photovoltaic cell working characteristics under the conditions of different illumination temperatures
CN108880469A (en) * 2018-04-20 2018-11-23 长安大学 A kind of method of solar battery parameter extraction
CN111506856A (en) * 2020-03-10 2020-08-07 燕山大学 Photovoltaic cell parameter identification method based on improved Harris eagle optimization algorithm

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104778352A (en) * 2015-03-31 2015-07-15 国家电网公司 Seven-parameter photovoltaic cell output characteristic modeling method based on STFT (Short Time Fourier Transform) operator
CN106468935A (en) * 2016-09-18 2017-03-01 中州大学 A kind of segmented fitting seeks solaode peak power point methods
CN108365822A (en) * 2018-04-12 2018-08-03 山东大学 The prediction technique and system of photovoltaic cell working characteristics under the conditions of different illumination temperatures
CN108880469A (en) * 2018-04-20 2018-11-23 长安大学 A kind of method of solar battery parameter extraction
CN111506856A (en) * 2020-03-10 2020-08-07 燕山大学 Photovoltaic cell parameter identification method based on improved Harris eagle optimization algorithm

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
一种求解光伏电池5 参数模型的方法;孔祥雨等;《电力***保护与控制》;20131116;第41卷(第22期);全文 *

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