CN106959707A - A kind of solar radiation quantity for photovoltaic generation monitors method of adjustment - Google Patents
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Abstract
Method of adjustment is monitored the invention discloses a kind of solar radiation quantity for photovoltaic generation.Preposition solar radiation quantity prediction, obtains sun apparent azimuth angle and per day approximate solar radiation quantity；Whether tracking is adjusted according to per day approximate solar radiation quantity and minimum tracking threshold decision；According to the azimuth of sun apparent azimuth angle coarse adjustment photovoltaic battery panel；According to the azimuth of solar radiation quantity sensor difference fine tuning photovoltaic battery panel.It is excessive that the present invention considers existing solar tracking system power consumption so that the defect that final generating efficiency is not improved, and adds preposition solar radiation quantity and predicts and set minimum tracking threshold value, improves the efficiency of photovoltaic generation.
Description
Technical field
The present invention relates to field of photovoltaic power generation, a kind of solar radiation quantity for photovoltaic generation has been specifically related to it and has monitored tune
Adjusting method.
Background technology
Under the background of new energy technology general development, many researchs for improving photovoltaic efficiency are occurred in that.It is main
Wanting research direction has several classes, and such as solar panel sets out in itself studies more new and effective solar cell plate material；
From solar radiation angle increase solar radiation area with receiving intensity of solar radiation, such as it can track solar energy orientation
Sun tracking system etc.., really can be with by adjusting the position of solar panel to increase solar radiation area and receiving intensity
More efficiently utilize solar power generation.
But according to existing technological means, the consumption of solar follow-up device is possible to than larger, or even is finally carried
High Solar use efficiency can not make up the consumption of this part, so a feasible method is to apply preposition prediction, on the one hand
The azimuth of pre- shoot the sun, the solar radiation quantity on the day of on the other hand predicting estimates the efficiency on the same day and the ratio consumed with this
Weight.
The content of the invention
The problem of for improving photovoltaic efficiency, the invention provides a kind of solar radiation quantity prison for photovoltaic generation
Method of adjustment is controlled, solar radiation quantity among a period of time is implemented to predict and monitored, photovoltaic battery panel is preferably adjusted
State, it is possible to increase photovoltaic efficiency.
As shown in figure 1, the technical scheme is that including following four part：
(1) preposition solar radiation quantity prediction, obtains sun apparent azimuth angle and per day approximate solar radiation quantity；
(2) whether tracking is adjusted according to per day approximate solar radiation quantity and minimum tracking threshold decision；
(3) according to the azimuth of sun apparent azimuth angle coarse adjustment photovoltaic battery panel；
(4) according to the azimuth of solar radiation quantity sensor difference fine tuning photovoltaic battery panel.
Described step (one) is specifically included：
(1.1) sample data is obtained from historical data base；
(1.2) sample data is pre-processed；
(1.3) sun apparent azimuth angle and per day approximate solar radiation are obtained using multiple linear regression analysis prediction
Amount.
Described historical data base refers to for somewhere under daily sunshine, daily not maximum solar amount institute in the same time
Azimuthal historical data, can be considered the sun just to azimuthal historical data base.
Described sample data refers to be predicted the same day corresponding orientation not in the same time where maximum solar amount
Angle, be specifically included in prediction day data a few days ago, earlier month with prediction day for corresponding same day data, several years ago in
With the data that prediction day is corresponding same day.
Described step (1.2) sample data pretreatment is the easy interference data for filtering out special weather cause influence.Tool
Body is removed from sample data because of the period of severe extreme weather or accidental weather corresponding data.Such as weather is disliked
The period such as bad, extreme, solar eclipse corresponding data.
Described step (1.3) is specifically to calculate to be predicted the same day using the multiple linear regression model of below equation
Sun apparent azimuth angle in the same time where maximum solar amount, for the prediction same day a certain moment ti, does not have：
Yt=a1x1+a2x2+…akxk+b
Wherein, ytThe Azimuth prediction value where ti moment maximum solars amount, x1,x2,......xkIt is respectively selected
The respective azimuth where ti moment maximum solars amount of different samples, k represents the sum of selected sample data, a1,
a2,......akRegression coefficient is, b is constant term.
To weigh the quality that predicts the outcome, some training numbers can be chosen in advance and take average absolute error to refer to as measurement
Mark.
It is possible thereby to azimuth where all maximum solar amounts not in the same time of the same day since sunrise is predicted,
It is at a time interval step-length to simplify algorithm, the data at prediction limited moment of the same day.For example since 6 points of sunrise, arrive
18 points of sunset, it 15 minutes is step-length that can choose, azimuth where the maximum solar amount at limited moment of prediction.
And per day approximate solar radiation quantity is tried to achieve according to the maximum solar amount calculating in sample data not in the same time.
Described step (two) judges whether per day approximate solar radiation quantity is more than minimum tracking threshold value, in order to
The energy that balance real-time tracking system is consumed and increased energy after the raising of photovoltaic cell plate efficiency.
Described step (two) is specially：
If per day approximate solar radiation quantity is more than minimum tracking threshold value, consider that photovoltaic cell plate efficiency is still after consuming
Increase, make photovoltaic battery panel could be adjusted to track the sun, carry out next step (three) and orientation is carried out to photovoltaic battery panel
The adjustment at angle；
If per day approximate solar radiation quantity is more than minimum tracking threshold value, photovoltaic cell plate efficiency, which is not improved, to put
Tracking is abandoned, the azimuth of photovoltaic battery panel is adjusted to middle position, towards the meridian hour sun institute to position.
Described step (three) is by the position corresponding to the position adjustment of photovoltaic battery panel to sun apparent azimuth angle.
Described step (four) is specifically divided into two steps：
(4.1) it is real by the radiation amount sensor installed in photovoltaic battery panel direction of rotation both sides (generally thing both sides)
When monitor solar radiation quantity data, obtain the difference of both sides solar radiation quantity.
(4.2) difference and then the processing of both sides solar radiation quantity are compared：
If the solar radiation quantity in east side is more than west side, side rotates adjustment photovoltaic battery panel eastwards so that both sides sun spoke
The difference for the amount of penetrating is in the range of discrepancy threshold；
If the solar radiation quantity in west side is more than east side, westwards side rotates adjustment photovoltaic battery panel so that both sides sun spoke
The difference for the amount of penetrating is in the range of discrepancy threshold.
The beneficial effects of the invention are as follows：
Than other method, the major advantage of the inventive method is：One is to add the prediction loop to solar radiation quantity
Section, is predicted using multiple linear regression model to the solar azimuth and per day approximate solar radiation quantity on the same day, is set
Whether minimum tracking threshold decision is tracked, and among state to the scope predicted of coarse adjustment photovoltaic battery panel；Two be in reality
When tracking process among can be according to the state of the solar radiation quantity sensing data fine tuning photovoltaic battery panel of both sides.
Scheme provided by the present invention can preferably adjust the state of photovoltaic battery panel, so as to improve solar power generation
Efficiency.
Brief description of the drawings
Fig. 1 is procedure chart of the invention.
Fig. 2 is sensor mounting location schematic diagram.
Fig. 3 is fine tuning photovoltaic battery panel detailed process figure.
Fig. 4 is surveyed and the figure that predicts the outcome for the solar azimuth of embodiment one day.
Embodiment
In order to more specifically describe the overall process of the present invention, below in conjunction with the accompanying drawings and embodiment is to the present invention
Technical scheme be described in detail.
Embodiments of the invention are as follows：
(1) preposition solar radiation quantity prediction, obtains sun apparent azimuth angle and per day approximate solar radiation quantity；
(1.1) sample data is obtained from historical data base；
For example, such as to predict the data on March 10th, 2017, following sample can be chosen from historical data：When a few days ago
Several days such as the data on March 9th, 1 day 1 March in 2017, the data related to the same day of earlier month such as 2017 2
Each five day data, each five day data before and after 10 days January in 2017, each five number of days before and after 10 days December in 2016 before and after the moon 10
According to data, data etc. before and after 10 days March in 2015 before and after same day data such as 10 days March in 2016 several years ago.
(1.2) sample data is pre-processed；
According to weather records, there is rainy weather in local on March 1st, 2017, so its data can be interfered to prediction,
It should be rejected among selected sample.The specific method of rejecting is the weather data for extracting each sample, and sets up a weather
Mass parameter, for weighing same day sky quality or other special and extreme environment influences.If the sky quality parameter
Just rejected less than a certain threshold value from selected sample data.
(1.3) sun apparent azimuth angle and per day approximate solar radiation are obtained using multiple linear regression analysis prediction
Amount.Each above-mentioned sample is subject to weight setting regression coefficient, substitutes among multivariate regression models and calculates to be predicted the same day not
Sun apparent azimuth angle where maximum solar amount in the same time.
And per day approximate solar radiation quantity is tried to achieve according to the maximum solar amount calculating in sample data not in the same time.
Specific implementation is that since 6 points of sunrise, to 18 points of sunset, it 15 minutes is step-length that can choose, and predicts the maximum at multiple moment too
Azimuth and per day approximate solar radiation quantity where positive amount of radiation.
(2) whether tracking is adjusted according to per day approximate solar radiation quantity and minimum tracking threshold decision；
If per day approximate solar radiation quantity is more than minimum tracking threshold value, next step (three) is carried out to photovoltaic battery panel
Carry out azimuthal adjustment；
If per day approximate solar radiation quantity is more than minimum tracking threshold value, the azimuth of photovoltaic battery panel is adjusted into
Position is entreated, towards the meridian hour sun institute to position.
(3) according to the azimuth of sun apparent azimuth angle coarse adjustment photovoltaic battery panel, by the position adjustment of photovoltaic battery panel extremely
Position corresponding to sun apparent azimuth angle.
(4) according to the azimuth of solar radiation quantity sensor difference fine tuning photovoltaic battery panel, two steps are specifically divided into：
(4.1) it is real-time by being arranged on the radiation amount sensor 1 and 2 of photovoltaic battery panel direction of rotation both sides as shown in Figure 2
Solar radiation quantity data are monitored, the difference of both sides solar radiation quantity is obtained.
(4.2) difference and then the processing of both sides solar radiation quantity are compared：
If the solar radiation quantity in east side is more than west side, side rotates adjustment photovoltaic battery panel eastwards so that both sides sun spoke
The difference for the amount of penetrating is in the range of discrepancy threshold；
If the solar radiation quantity in west side is more than east side, westwards side rotates adjustment photovoltaic battery panel so that both sides sun spoke
The difference for the amount of penetrating is in the range of discrepancy threshold.
Specific implementation is that single-chip microcomputer enters as shown in figure 3, data are reached single-chip microcomputer by two side sensers by A/D converter circuit
Row calculates the solar radiation quantity difference of both sides, and sets discrepancy threshold, and electricity is controlled if both sides difference exceedes discrepancy threshold
Machine rotation adjustment photovoltaic cell Board position.
Be predicted according to the method described above, obtain one day solar azimuth actual measurement with predict the outcome as shown in figure 4, and
The photovoltaic efficiency on the same day is also significantly increased compared to other dates of similar weather conditions after being tracked.
As can be seen here, the present invention can improve generating efficiency, and consider existing solar tracking system power consumption well
It is excessive so that the defect that final generating efficiency is not improved, add preposition solar radiation quantity and predict and set minimum tracking
Threshold value, can finally improve the efficiency of photovoltaic generation.
Claims (9)
1. a kind of solar radiation quantity for photovoltaic generation monitors method of adjustment, it is characterised in that method includes following four portion
Point：
(1) preposition solar radiation quantity prediction, obtains sun apparent azimuth angle and per day approximate solar radiation quantity；
(2) whether tracking is adjusted according to per day approximate solar radiation quantity and minimum tracking threshold decision；
(3) according to the azimuth of sun apparent azimuth angle coarse adjustment photovoltaic battery panel；
(4) according to the azimuth of solar radiation quantity sensor difference fine tuning photovoltaic battery panel.
2. a kind of solar radiation quantity for photovoltaic generation according to claim 1 monitors method of adjustment, it is characterised in that：
Described step (one) is specifically included：
(1.1) sample data is obtained from historical data base；
(1.2) sample data is pre-processed；
(1.3) sun apparent azimuth angle and per day approximate solar radiation quantity are obtained using multiple linear regression analysis prediction.
3. a kind of solar radiation quantity for photovoltaic generation according to claim 2 monitors method of adjustment, it is characterised in that：
Described historical data base refers under daily sunshine, daily azimuthal history not in the same time where maximum solar amount
Data.
4. a kind of solar radiation quantity for photovoltaic generation according to claim 2 monitors method of adjustment, it is characterised in that：
Described sample data refers to be predicted the same day corresponding azimuth not in the same time where maximum solar amount, specific to wrap
Include prediction day data a few days ago, in earlier month with prediction day for corresponding same day data, several years ago in predicting day
For the data of correspondence same day.
5. a kind of solar radiation quantity for photovoltaic generation according to claim 2 monitors method of adjustment, it is characterised in that：
Described step (1.2) sample data pretreatment is the easy interference data for filtering out special weather cause influence.
6. a kind of solar radiation quantity for photovoltaic generation according to claim 2 monitors method of adjustment, it is characterised in that：
Described step (1.3) be specifically calculated using the multiple linear regression model of below equation to be predicted the same day not in the same time
Sun apparent azimuth angle where maximum solar amount, for the prediction same day a certain moment ti, has：
Yt=a1x1+a2x2+ ... akxk+b
Wherein, ytThe Azimuth prediction value where ti moment maximum solars amount, x1,x2,......xkRespectively it is selected not
With azimuth where sample each ti moment maximum solars amount, k represents the sum of selected sample data, a1,a2,
......akRegression coefficient is, b is constant term；
And per day approximate solar radiation quantity is tried to achieve according to the maximum solar amount calculating in sample data not in the same time.
7. a kind of solar radiation quantity for photovoltaic generation according to claim 1 monitors method of adjustment, it is characterised in that：
Described step (two) is specially：
If per day approximate solar radiation quantity is more than minimum tracking threshold value, carries out next step (three) and photovoltaic battery panel is carried out
Azimuthal adjustment；
If per day approximate solar radiation quantity is more than minimum tracking threshold value, the azimuth of photovoltaic battery panel is adjusted to central position
Put, towards the meridian hour sun institute to position.
8. a kind of solar radiation quantity for photovoltaic generation according to claim 1 monitors method of adjustment, it is characterised in that：
Described step (three) is by the position corresponding to the position adjustment of photovoltaic battery panel to sun apparent azimuth angle.
9. a kind of solar radiation quantity for photovoltaic generation according to claim 1 monitors method of adjustment, it is characterised in that：
Described step (four) is specifically divided into two steps：
(4.1) solar radiation quantity number is monitored by the radiation amount sensor installed in photovoltaic battery panel direction of rotation both sides in real time
According to obtaining the difference of both sides solar radiation quantity.
(4.2) difference and then the processing of both sides solar radiation quantity are compared：
If the solar radiation quantity in east side is more than west side, side rotates adjustment photovoltaic battery panel eastwards so that both sides solar radiation quantity
Difference in the range of discrepancy threshold；
If the solar radiation quantity in west side is more than east side, westwards side rotates adjustment photovoltaic battery panel so that both sides solar radiation quantity
Difference in the range of discrepancy threshold.
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| CN107632621A (en) * | 2017-10-25 | 2018-01-26 | 上海瀛为智能科技有限责任公司 | Hull and ship with solar energy automatic tracking |
| CN109884896A (en) * | 2019-03-12 | 2019-06-14 | 河海大学常州校区 | A kind of photovoltaic tracking system optimization tracking based on similar day irradiation prediction |
| CN112292812A (en) * | 2018-05-18 | 2021-01-29 | 耐克斯特拉克尔有限公司 | Method and system for detecting shadows of solar trackers |
| CN112379698A (en) * | 2020-11-25 | 2021-02-19 | 浙江大学建筑设计研究院有限公司 | Automatic photovoltaic system of tracking |
| CN112882497A (en) * | 2021-01-21 | 2021-06-01 | 辽宁太阳能研究应用有限公司 | Angle-advancing type photovoltaic system adjusting method |
| CN116054738A (en) * | 2023-03-21 | 2023-05-02 | 呼和浩特市语能科技有限责任公司 | Solar power generation monitoring management system and method of Internet of things |
| CN117767295A (en) * | 2023-12-25 | 2024-03-26 | 泰富江苏共享网络科技有限公司 | Method for predictive analysis of stable power generation time period of photovoltaic power station |
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| CN116054738A (en) * | 2023-03-21 | 2023-05-02 | 呼和浩特市语能科技有限责任公司 | Solar power generation monitoring management system and method of Internet of things |
| CN116054738B (en) * | 2023-03-21 | 2023-12-29 | 荣达通(北京)能源有限公司 | Solar power generation monitoring management system and method of Internet of things |
| CN117767295A (en) * | 2023-12-25 | 2024-03-26 | 泰富江苏共享网络科技有限公司 | Method for predictive analysis of stable power generation time period of photovoltaic power station |
| CN117767295B (en) * | 2023-12-25 | 2024-08-06 | 泰富江苏共享网络科技有限公司 | Method for predictive analysis of stable power generation time period of photovoltaic power station |
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