CN110059446A - A method of prediction photovoltaic module dust stratification degree - Google Patents
A method of prediction photovoltaic module dust stratification degree Download PDFInfo
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- CN110059446A CN110059446A CN201910414352.4A CN201910414352A CN110059446A CN 110059446 A CN110059446 A CN 110059446A CN 201910414352 A CN201910414352 A CN 201910414352A CN 110059446 A CN110059446 A CN 110059446A
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Abstract
The invention discloses a kind of methods for predicting photovoltaic module dust stratification degree, specifically, comparing component according to photovoltaic, i.e. the operating current of cleaning assemblies and dust stratification component calculates the real-time dust stratification degree of photovoltaic module；The dust stratification degree that is averaged in a short time is found out, base data is established；Secondly, establishing a kind of model for predicting photovoltaic module dust stratification degree, the dust stratification degree at some following time point is calculated according to future weather conditions.The present invention predicts photovoltaic module dust stratification degree, lays a good foundation for the judgement and prediction of component dust stratification scavenging period point.
Description
Technical field
The present invention relates to a kind of methods for predicting photovoltaic module dust stratification degree, belong to solar energy photovoltaic system application technology neck
Domain.
Background technique
Photovoltaic module superficial dust will affect the light transmittance of photovoltaic module watch crystal, and it is strong to reduce component reception solar irradiation
Degree, in addition, assembly surface temperature increases if clearing up dust stratification not in time, melts dust stratification to reduce the generating efficiency of component
Change, bonding, so that " hot spot effect " is generated, and at acidic materials meeting eroded components in dust stratification, so to sum up, dust stratification is existing
As bringing biggish economic loss to photovoltaic module power generation.
Currently, photovoltaic dust stratification problem has become a focus of photovoltaic industry, dust stratification scavenging period point also becomes people
How urgent problem determines that dust stratification scavenging period point first has to whether determination component needs to clean, that is, can determine whether photovoltaic
Whether assembly surface dust stratification degree reaches necessity of cleaning, so how photovoltaic plant urgent need predicts light under some following time point
The method for lying prostrate the dust stratification degree of component brings guiding significance for photovoltaic plant operation.
Summary of the invention
Problem to be solved by this invention is to overcome the deficiencies of existing technologies, and provides a kind of prediction photovoltaic module dust stratification degree
Method the dust stratification degree at certain following moment of component can be calculated according to the weather condition of predictions for future.
In order to solve the above technical problems, the technical solution adopted by the present invention are as follows:
A method of prediction photovoltaic module dust stratification degree, comprising the following steps:
1) the real-time dust stratification degree of photovoltaic module is calculated:
Wherein, ηiFor the real-time dust stratification degree of photovoltaic module under i-th of data point, ζ is the initial calibration factor, I1i、I2iRespectively
For the output electric current under i-th of data point of cleaning assemblies and dust stratification component, i is that data take an order；
2) it is based on the real-time dust stratification degree of photovoltaic module, calculates the substrate coefficient η of prediction photovoltaic module dust stratification degree0:
Wherein, m is that the data of the real-time dust stratification degree of photovoltaic module in certain time period t take a number；
3) photovoltaic module dust stratification degree prediction model is constructed:
ηf=η0·ln(α·N)
Wherein, ηfFor the dust stratification degree at certain time point of prediction, N is total correction factor, certain time predicted as needed
The weather condition of point calculates, and α is modifying factor,
The calculating of N is as follows:
Wherein,For the air quality correction factor at certain time point,For the air humidity correction factor at certain time point,For the wind correction coefficient at certain time point,For the rainfall quantity correction coefficient at certain time point.
In aforementioned step 1), initial calibration factor ζ calculates as follows:
Wherein, I01、I02It is expressed as the short circuit electricity that cleaning assemblies and dust stratification component are tested under the conditions of primary standard
Stream.
Cleaning assemblies and dust stratification component above-mentioned is consistent with the mounted angle of photovoltaic module in local photovoltaic system.
Time period t above-mentioned takes a hour.
Time period t above-mentioned is chosen between 10.00am -14.00pm.
The value range of m above-mentioned is 50-70, chooses data by isochronal differences and takes a little.
Modifying factor α value range above-mentioned is 1.1~1.5.
Air quality correction factor value above-mentioned is as follows:
Air quality grade is excellent:
Air quality grade is good:
Air quality grade is slight pollution:
Air quality grade is intermediate pollution:
Air quality grade is serious pollution:
Wherein, air quality grade is determined according to China Meteorological data network.
Air humidity correction factor value above-mentioned is as follows:
Air humidity is 0~30%:
Air humidity is 30~60%:
Air humidity is 60~90%:
Wherein, air humidity is determined according to China Meteorological data network.
Wind correction coefficient value above-mentioned is as follows:
Wind-force is 1~2 grade:
Wind-force is 3~4 grades:
Wind-force is 5~6 grades:
Wind-force is 7~8 grades:
Wherein, wind scale is determined according to China Meteorological data network.
Rainfall quantity correction coefficient value above-mentioned is as follows:
Rainfall < Dmm:
Dmm < rainfall < Emm:
Emm < rainfall:
Wherein, rainfall is determined according to China Meteorological data network；D takes 2~4, E to take 9~11.
Advantageous effects of the invention:
The present invention can use the weather condition data predicted in real time, pass through the dust stratification degree prediction model meter of photovoltaic module
Calculation obtains the dust stratification degree of the following different time points, so as to judge whether clean in several days following according to dust stratification degree, or
Person judges scavenging period point next time, and the meaning of directiveness is played for photovoltaic module scavenging period point.
Detailed description of the invention
Fig. 1 is present invention prediction photovoltaic module dust stratification degree flow chart；
Fig. 2 is present invention dust stratification degree detection device figure in real time；
Fig. 3 is practical dust stratification degree and prediction dust stratification level data comparison diagram in embodiment.
Specific embodiment
The invention will be further described below.Following embodiment is only used for clearly illustrating technical side of the invention
Case, and not intended to limit the protection scope of the present invention.
The present invention provides a kind of method for predicting photovoltaic module dust stratification degree, referring to Fig. 1 and Fig. 2, including following portion
Point:
1, the model of the real-time dust stratification degree of photovoltaic module is established, detailed process is as follows:
1-1) calculate the real-time dust stratification degree of photovoltaic module:
Wherein, ζ is the initial calibration factor, ηiFor the real-time dust stratification degree of photovoltaic module under i-th of data point,
I1i、I2iThe output electric current being expressed as under i-th of data point of cleaning assemblies and dust stratification component, i are that data take a little
Order.Output electric current is measured using detection device shown in Fig. 2.
In the detection device, cleaning assemblies and dust stratification component are consistent with the local medium-and-large-sized component mounted angle of photovoltaic system.
Also, cleaning assemblies needs fixed time cleaning in this step.
1-2) calculate initial calibration factor ζ are as follows:
Wherein, I01、I02It is expressed as the short circuit electricity that cleaning assemblies and dust stratification component are tested under the conditions of primary standard
Stream.
2, the average dust stratification degree of photovoltaic module is calculated, and as substrate coefficient η0:
Wherein, m is that the data of the real-time dust stratification degree of photovoltaic module in certain time period t take a number, and t suggestion takes one small
When, m is chosen between 50-70, it is proposed that isochronal differences are chosen, and time period t is chosen between 10.00am -14.00pm, wherein i
An order is taken for data, from 1~m.
3, each correction factor is determined:
3-1) determine air quality correction factor
Air quality grade is excellent:
Air quality grade is good:
Air quality grade is slight pollution:
Air quality grade is intermediate pollution:
Air quality grade is serious pollution:
Wherein air quality grade is determined according to China Meteorological data network.
3-2) determine air humidity correction factor
Air humidity is 0~30%:
Air humidity is 30~60%:
Air humidity is 60~90%:
Wherein, air humidity is determined according to China Meteorological data network.
3-3) determine wind correction coefficient
Wind-force is 1~2 grade:
Wind-force is 3~4 grades:
Wind-force is 5~6 grades:
Wind-force is 7~8 grades:
Wherein, wind scale is determined according to China Meteorological data network.
3-4) determine rainfall quantity correction coefficient
Rainfall < Dmm:
It is at this time no cleaning effect, photovoltaic module dust stratification is cleaned without influence in rainfall in this case, photovoltaic module after rainfall
Dust stratification degree is unchanged；
Dmm < rainfall < Emm:
It is at this time micro- cleaning effect, rainfall has certain cleaning ability, photovoltaic after rainfall to photovoltaic module dust stratification in this case
The dust stratification degree of component will reduce to a certain degree；
Emm < rainfall:
It is at this time complete cleaning effect, dust stratification is completely removed in this case, and the dust stratification degree of photovoltaic module will after rainfall
It is set as 0；
Wherein, rainfall is determined according to China Meteorological data network；
Wherein, D takes 2~4, E to take 9~11.
4, photovoltaic module dust stratification degree prediction model is established:
4-1) photovoltaic module prediction dust stratification degree calculates as follows:
ηf=η0·ln(α·N) (4)
Wherein, ηfFor the dust stratification degree at certain time point of prediction, N is total correction factor, certain time predicted as needed
The weather condition of point calculates, and α is modifying factor；
Wherein, modifying factor α takes 1.1~1.5；
4-2) calculate total correction factor N:
Wherein,For air quality correction factor,For air humidity correction factor,For wind correction coefficient,For
Rainfall quantity correction coefficient.
The dust stratification degree of photovoltaic module under following some time point in a short time can be obtained by above step.It is general predictable
Dust stratification degree in 1 week.
In order to verify the accuracy and feasibility of the method for the present invention, choose random between Changzhou Prefecture 2018.09~2018.11
Data, calculate the photovoltaic module dust stratification degree in opposite access time point future using the present invention, and with the experimental data of detection into
Row comparison, from the figure 3, it may be seen that the present invention and the prediction dust stratification degree that measurement method obtains are almost the same, can only go out in certain days
The situation that existing data have deviation larger, but global consistency is preferable.
The present invention is suitable for predicting calculating the dust stratification degree of photovoltaic module under some following time point, and calculated result reflects
Reference value and applicability of the invention.
The above is only superior embodiment of the invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, several improvement and deformations can also be made, these improvement and deformations
Also it should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of method for predicting photovoltaic module dust stratification degree, which comprises the following steps:
1) the real-time dust stratification degree of photovoltaic module is calculated:
Wherein, ηiFor the real-time dust stratification degree of photovoltaic module under i-th of data point, ζ is the initial calibration factor, I1i、I2iIt is respectively clear
Output electric current under i-th of data point of clean component and dust stratification component, i are that data take an order；
2) it is based on the real-time dust stratification degree of photovoltaic module, calculates the substrate coefficient η of prediction photovoltaic module dust stratification degree0:
Wherein, m is that the data of the real-time dust stratification degree of photovoltaic module in certain time period t take a number；
3) photovoltaic module dust stratification degree prediction model is constructed:
ηf=η0·ln(α·N)
Wherein, ηfFor the dust stratification degree at certain time point of prediction, N is total correction factor, the day at certain time point predicted as needed
Gas situation calculates, and α is modifying factor,
The calculating of N is as follows:
Wherein,For the air quality correction factor at certain time point,For the air humidity correction factor at certain time point,For
The wind correction coefficient at certain time point,For the rainfall quantity correction coefficient at certain time point.
2. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the step 1)
In, initial calibration factor ζ calculates as follows:
Wherein, I01、I02It is expressed as the short circuit current that cleaning assemblies and dust stratification component are tested under the conditions of primary standard.
3. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the cleaning group
Part and dust stratification component are consistent with the mounted angle of photovoltaic module in local photovoltaic system.
4. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the period
T chooses between 10.00am -14.00pm；The time period t takes a hour.
5. a kind of method for predicting photovoltaic module dust stratification degree according to claim 4, which is characterized in that the m's takes
Value range is 50-70, chooses data by isochronal differences and takes a little.
6. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the modifying factor
Sub- α value range is 1.1~1.5.
7. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the air matter
Quantity correction coefficient value is as follows:
Air quality grade is excellent:
Air quality grade is good:
Air quality grade is slight pollution:
Air quality grade is intermediate pollution:
Air quality grade is serious pollution:
Wherein, air quality grade is determined according to China Meteorological data network.
8. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the air is wet
It is as follows to spend correction factor value:
Air humidity is 0~30%:
Air humidity is 30~60%:
Air humidity is 60~90%:
Wherein, air humidity is determined according to China Meteorological data network.
9. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the wind-force is repaired
Positive coefficient value is as follows:
Wind-force is 1~2 grade:
Wind-force is 3~4 grades:
Wind-force is 5~6 grades:
Wind-force is 7~8 grades:
Wherein, wind scale is determined according to China Meteorological data network.
10. a kind of method for predicting photovoltaic module dust stratification degree according to claim 1, which is characterized in that the rainfall
Quantity correction coefficient value is as follows:
Rainfall < Dmm:
Dmm < rainfall < Emm:
Emm < rainfall:
Wherein, rainfall is determined according to China Meteorological data network；D takes 2~4, E to take 9~11.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111985732A (en) * | 2020-09-10 | 2020-11-24 | 浙江正泰新能源开发有限公司 | Photovoltaic module contamination degree prediction method and system |
| CN112326684A (en) * | 2020-10-21 | 2021-02-05 | 阳光电源股份有限公司 | Photovoltaic module dust accumulation detection method, device, equipment and storage medium |
| CN112671337A (en) * | 2020-12-29 | 2021-04-16 | 新奥数能科技有限公司 | Method and device for determining whether photovoltaic panel needs to be cleaned |
| CN113393046A (en) * | 2021-06-23 | 2021-09-14 | 阳光电源股份有限公司 | Photovoltaic power prediction method and application device thereof |
| CN114118561A (en) * | 2021-11-22 | 2022-03-01 | 华能山东发电有限公司众泰电厂 | Photovoltaic module cleaning method and system considering dust deposition |
-
2019
- 2019-05-17 CN CN201910414352.4A patent/CN110059446A/en not_active Withdrawn
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111985732A (en) * | 2020-09-10 | 2020-11-24 | 浙江正泰新能源开发有限公司 | Photovoltaic module contamination degree prediction method and system |
| CN111985732B (en) * | 2020-09-10 | 2023-08-29 | 浙江正泰新能源开发有限公司 | Photovoltaic module pollution degree prediction method and system |
| CN112326684A (en) * | 2020-10-21 | 2021-02-05 | 阳光电源股份有限公司 | Photovoltaic module dust accumulation detection method, device, equipment and storage medium |
| CN112326684B (en) * | 2020-10-21 | 2022-05-24 | 阳光电源股份有限公司 | Photovoltaic module dust accumulation detection method, device, equipment and storage medium |
| CN112671337A (en) * | 2020-12-29 | 2021-04-16 | 新奥数能科技有限公司 | Method and device for determining whether photovoltaic panel needs to be cleaned |
| CN112671337B (en) * | 2020-12-29 | 2024-05-14 | 新奥数能科技有限公司 | Method and device for determining whether photovoltaic panel needs cleaning |
| CN113393046A (en) * | 2021-06-23 | 2021-09-14 | 阳光电源股份有限公司 | Photovoltaic power prediction method and application device thereof |
| CN114118561A (en) * | 2021-11-22 | 2022-03-01 | 华能山东发电有限公司众泰电厂 | Photovoltaic module cleaning method and system considering dust deposition |
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Application publication date: 20190726 |