CN111258335A - Photovoltaic tracking optimization method, device and system and storage medium - Google Patents
Photovoltaic tracking optimization method, device and system and storage medium Download PDFInfo
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Abstract
The invention discloses a photovoltaic tracking optimization method, a photovoltaic tracking optimization device, a photovoltaic tracking optimization system and a storage medium, wherein the method comprises the following steps: acquiring a predicted angle parameter and a predicted meteorological parameter; inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result; adjusting the photovoltaic module according to the predicted output result; the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed. According to the invention, the angle parameter is added into the prediction model, so that the prediction model can predict the irradiation according to the angle of the sun, the accuracy of solar irradiation prediction is improved, and the tracking efficiency of the photovoltaic tracking system is improved. The invention can be widely applied to the field of photovoltaic power generation.
Description
Technical Field
The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic tracking optimization method, device and system and a storage medium.
Background
The solar photovoltaic power generation has the advantages of high photoelectric conversion efficiency, no pollution and noise in the power generation process, long service life and the like. At present, the installed capacity of photovoltaic power generation of various countries in the world is steadily increased, and in order to further improve the generated energy of a photovoltaic power station, the existing photovoltaic module is generally provided with a corresponding tracking system. Generally, tracking technology can increase the power generation capacity of a photovoltaic system, but in cloudy and cloudy conditions, the tracking system does not necessarily provide additional gain and additional power consumption to the photovoltaic system. The existing photovoltaic tracking system predicts irradiation through meteorological parameters, but the irradiation cannot be well predicted by a meteorological parameter-based prediction method, the main prediction focus is the influence of the meteorological parameters on the irradiation, the irradiation is not accurately predicted, and the tracking efficiency of the photovoltaic tracking system is low.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, a system and a storage medium for optimizing photovoltaic tracking, so as to improve the tracking efficiency of a photovoltaic tracking system.
The first technical scheme adopted by the invention is as follows:
a photovoltaic tracking optimization method comprises the following steps:
acquiring a predicted angle parameter and a predicted meteorological parameter;
inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result;
adjusting the photovoltaic module according to the predicted output result;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
Further, the photovoltaic tracking optimization model is a logistic regression model.
Further, the adjusting the photovoltaic module according to the predicted output result specifically includes:
when the predicted output result is a first result, adjusting the photovoltaic module to rotate to a fixed installation position;
and when the predicted output result is a second result, tracking the photovoltaic module according to a preset program.
Further:
when the photovoltaic tracking system is used for double-axis tracking, the fixed installation position is the optimal inclination angle of the installation place;
when the photovoltaic tracking system is in flat single-axis tracking, the fixed installation position is horizontal installation;
when the photovoltaic tracking system is used for tracking the inclined single shaft, the fixed installation position is the optimal inclination angle of the installation place.
Further, the training steps of the photovoltaic tracking optimization model are as follows:
acquiring a plurality of groups of training samples, wherein each group of training samples comprises input parameters and output parameters, the input parameters comprise meteorological parameters and angle parameters, and the output parameters comprise comparison results of power generation benefits of the photovoltaic modules fixedly installed under the conditions of the meteorological parameters and the angle parameters and power generation benefits of the tracking photovoltaic modules;
training a photovoltaic tracking optimization model according to the training sample to obtain a trained photovoltaic tracking optimization model; the comparison result of the power generation benefit of the fixedly installed photovoltaic module and the power generation benefit of the tracking photovoltaic module is as follows: and when the power generation benefit of the fixedly installed photovoltaic module is greater than or equal to the power generation benefit of the tracking photovoltaic module, recording the comparison result as a first result, and when the power generation benefit of the fixedly installed photovoltaic module is less than the power generation benefit of the tracking photovoltaic module, recording the comparison result as a second result.
Further, the angle parameter, the meteorological parameter, the predicted angle parameter and the predicted meteorological parameter are all subjected to normalization processing.
Further, the power generation benefit of the tracking photovoltaic module is the difference value between the total power generation amount of the tracking photovoltaic module and the power consumption consumed by tracking the tracking photovoltaic module.
The second technical scheme adopted by the invention is as follows:
a photovoltaic tracking optimization apparatus, comprising:
the processor is used for acquiring a predicted angle parameter and a predicted meteorological parameter, inputting the predicted meteorological parameter and the predicted angle parameter into a trained photovoltaic tracking optimization model, acquiring a predicted output result, and adjusting the photovoltaic module according to the predicted output result;
the photovoltaic module is used for converting solar energy into electric energy;
the supporting shaft seat is used for controlling the orientation of the photovoltaic module according to the output of the processor;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
The third technical scheme adopted by the invention is as follows:
a photovoltaic tracking optimization system, comprising:
the acquisition module is used for acquiring the predicted angle parameter and the predicted meteorological parameter;
the processing module is used for inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result;
the execution module is used for adjusting the photovoltaic module according to the prediction output result;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
The fourth technical scheme adopted by the invention is as follows:
a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of photovoltaic tracking optimization as set forth.
Compared with the prior art, the angle parameter is added into the prediction model, so that the prediction model can predict the irradiation according to the angle of the sun, the accuracy of solar irradiation prediction is improved, and the tracking efficiency of the photovoltaic tracking system is improved.
Drawings
Fig. 1 is a block diagram illustrating steps of a photovoltaic tracking optimization method according to an embodiment of the present invention.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the schemes and the effects of the present invention.
The embodiment of the invention provides a photovoltaic tracking optimization method, which comprises the following steps with reference to fig. 1:
s1, acquiring a predicted angle parameter and a predicted meteorological parameter;
s2, inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result;
s3, adjusting the photovoltaic module according to the predicted output result;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
Specifically, a prediction angle parameter and a prediction meteorological parameter are obtained through a network and input into a trained photovoltaic tracking optimization model, and an output result is obtained to adjust the photovoltaic module. In this embodiment, the prediction can be performed using data of one hour in the future, and the influence of prediction error can be reduced by a shorter prediction time, thereby improving the prediction accuracy.
Angular parameters, including solar hour angle ωsSin α for solar altitudesAnd sun azimuth angle cos γsThe calculation formula of the three angle parameters is as follows:
ωs＝15×(ST-12)
wherein, when ST is true sun,
is latitude, and n is the serial number of the date in one year; by addingThe solar time angle, the solar altitude angle and the solar azimuth angle are used as prediction parameters, the influence of the solar angle on the photovoltaic module can be predicted, and fine adjustment of the photovoltaic module in hours or smaller time units can be realized due to the addition of the angle parameters.
The meteorological parameters comprise temperature, humidity and wind speed, the average temperature, humidity and wind speed parameters of the photovoltaic module are obtained from the outside and are used as prediction parameters, and the influence of the meteorological parameters on the photovoltaic module can be predicted.
The photovoltaic tracking optimization model is used for predicting the optimal photovoltaic operation strategy, and the optimal photovoltaic operation strategy is predicted by relying on meteorological parameters and angle parameters.
Further as an optional embodiment, the photovoltaic tracking optimization model is a logistic regression model.
Specifically, logistic regression is also called logistic regression analysis, and is a generalized linear regression analysis model, and is commonly used in the fields of data mining, automatic disease diagnosis, economic prediction and the like. In the embodiment, the logistic regression is used to predict the dependent variable as a classified variable of two classes, that is, the comparison result of the power generation benefit of the fixed installation position of the photovoltaic module and the power generation benefit tracked according to the preset program is used as the dependent variable of two classes.
As a further optional implementation manner, the adjusting the photovoltaic module according to the prediction output result specifically includes:
when the predicted output result is a first result, adjusting the photovoltaic module to rotate to a fixed installation position;
and when the predicted output result is a second result, tracking the photovoltaic module according to a preset program.
Specifically, corresponding to the building process of the logistic regression model, in the building process, data of the power generation benefit of the fixed mounting position of the photovoltaic module, which is greater than or equal to the power generation benefit tracked according to a preset program, is calibrated to be a first result, and when the obtained prediction output result is the first result, the power generation benefit of the fixed mounting position of the photovoltaic module is predicted to be greater than or equal to the power generation benefit tracked according to the preset program, and the photovoltaic module is controlled to be rotated to the fixed mounting position; and in the construction process, data of the power generation income of the fixed installation position of the photovoltaic module, which is less than the power generation income tracked according to the preset program, is marked as a second result, and when the obtained prediction output result is the second result, the power generation income of the fixed installation position of the photovoltaic module is predicted to be less than the power generation income tracked according to the preset program, and the photovoltaic module is controlled to track according to the prediction program. In this embodiment, the first result is 0 and the second result is 1.
Further optional embodiments:
when the photovoltaic tracking system is used for double-axis tracking, the fixed installation position is the optimal inclination angle of the installation place;
when the photovoltaic tracking system is in flat single-axis tracking, the fixed installation position is horizontal installation;
when the photovoltaic tracking system is used for tracking the inclined single shaft, the fixed installation position is the optimal inclination angle of the installation place.
Specifically, in the design of the photovoltaic array, if a fixed installation mode is adopted, there is a concept of an optimal inclination angle, wherein the optimal inclination angle refers to that the total annual radiation amount on the inclined surface of the photovoltaic panel reaches the maximum when the photovoltaic array is inclined according to a certain angle.
According to the difference of the photovoltaic tracking systems, the fixed installation positions of the photovoltaic modules are different, and when the photovoltaic tracking systems are used for double-axis tracking, the optimal fixed installation position is an optimal inclination angle obtained according to historical data; when the photovoltaic tracking system is a flat single-axis tracking system, the photovoltaic tracking system has one degree of freedom, and the optimal fixed installation position is horizontal installation; when the photovoltaic tracking system is a diagonal single-axis tracking system, which has one degree of freedom, the optimal fixed mounting position should be an optimal inclination angle derived from historical data.
As a further optional implementation, the training step of the photovoltaic tracking optimization model is as follows:
acquiring a plurality of groups of training samples, wherein each group of training samples comprises input parameters and output parameters, the input parameters comprise meteorological parameters and angle parameters, and the output parameters comprise comparison results of power generation benefits of the photovoltaic modules fixedly installed under the conditions of the meteorological parameters and the angle parameters and power generation benefits of the tracking photovoltaic modules;
training a photovoltaic tracking optimization model according to the training sample to obtain a trained photovoltaic tracking optimization model; the comparison result of the power generation benefit of the fixedly installed photovoltaic module and the power generation benefit of the tracking photovoltaic module is as follows: and when the power generation benefit of the fixedly installed photovoltaic module is greater than or equal to the power generation benefit of the tracking photovoltaic module, recording the comparison result as a first result, and when the power generation benefit of the fixedly installed photovoltaic module is less than the power generation benefit of the tracking photovoltaic module, recording the comparison result as a second result.
Specifically, historical meteorological parameters and historical angle parameters of the place are used as input parameters, the comparison result of the power generation benefits of the fixed installation photovoltaic module and the power generation benefits of the tracking photovoltaic module is used as output parameters, and the model is trained, so that the trained model can predict the advantages and disadvantages of the power generation benefits of the fixed installation photovoltaic module and the power generation benefits of the tracking photovoltaic module under the specified condition according to the meteorological parameters and the angle parameters.
Further as an optional implementation manner, the angle parameter, the meteorological parameter, the predicted angle parameter and the predicted meteorological parameter are all subjected to normalization processing.
Specifically, the normalized formula is as follows:
wherein, XnFor the normalized result, X is the value to be normalized, XminFor the minimum in the normalized data of the same type, XmaxIs the maximum value in the same type of data for normalization.
By carrying out normalization processing on the data, the convergence speed and accuracy of the photovoltaic tracking optimization model can be improved.
Further as an optional embodiment, the power generation benefit of the tracking photovoltaic module is a difference between the total power generation amount of the tracking photovoltaic module and the power consumption amount consumed by the tracking photovoltaic module for tracking.
Specifically, the tracking photovoltaic module is a single photovoltaic module for tracking in the photovoltaic tracking system, and the difference value between the total electric quantity generated by power generation of the tracking photovoltaic module and the electric quantity consumed by tracking is used as the power generation benefit of the tracking photovoltaic module, so that the power generation benefit is more accurate compared with the situation that the total electric quantity generated by power generation is directly used as the power generation benefit.
The embodiment of the present invention further provides a photovoltaic tracking optimization apparatus, including:
the processor is used for acquiring a predicted angle parameter and a predicted meteorological parameter, inputting the predicted meteorological parameter and the predicted angle parameter into a trained photovoltaic tracking optimization model, acquiring a predicted output result, and adjusting the photovoltaic module according to the predicted output result;
the photovoltaic module is used for converting solar energy into electric energy;
the supporting shaft seat is used for controlling the orientation of the photovoltaic module according to the output of the processor;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
Specifically, the contents in the above method embodiments are all applicable to the present apparatus embodiment, the functions specifically implemented by the present apparatus embodiment are the same as those in the above method embodiments, and the advantageous effects achieved by the present apparatus embodiment are also the same as those achieved by the above method embodiments.
The invention also provides a photovoltaic tracking optimization system, which comprises:
the acquisition module is used for acquiring the predicted angle parameter and the predicted meteorological parameter;
the processing module is used for inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result;
the execution module is used for adjusting the photovoltaic module according to the prediction output result;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
In particular, the data processing flows performed by the layers, modules, units, and/or platforms included in the system of embodiments of the invention may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The data processing flows correspondingly performed by the layers, modules, units and/or platforms included in the system of embodiments of the invention may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or a combination thereof. The computer program includes a plurality of instructions executable by one or more processors.
The invention also provides a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the method of photovoltaic tracking optimization.
In particular, the storage medium stores processor-executable instructions, which when executed by a processor are configured to perform the steps of the method for processing mutual information according to any one of the above-mentioned method embodiments. For the storage medium, it may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. It can be seen that the contents in the foregoing method embodiments are all applicable to this storage medium embodiment, the functions specifically implemented by this storage medium embodiment are the same as those in the foregoing method embodiments, and the advantageous effects achieved by this storage medium embodiment are also the same as those achieved by the foregoing method embodiments.
The invention provides a photovoltaic tracking optimization method based on meteorological parameters and angle parameters, which can realize the prediction of the power generation power of components in two different installation modes, namely a fixed installation mode and a tracking mode, and the maximization of the power generation capacity of a photovoltaic system through a large amount of historical data and a logistic regression classification algorithm model. Compared with the existing photovoltaic array installation mode, the photovoltaic array installation mode has the beneficial effects that: according to the photovoltaic system tracking optimization method based on the small-scale irradiation prediction, the temperature, humidity and wind speed data are collected at fixed points for a long time, the time angle, the altitude angle and the azimuth angle at the corresponding moment are calculated, a logistic regression classification model is used, the model is trained through a large amount of data, and the prediction precision is effectively improved.
The above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention as long as the technical effects of the present invention are achieved by the same means. The invention is capable of other modifications and variations in its technical solution and/or its implementation, within the scope of protection of the invention.
Claims (10)
1. A photovoltaic tracking optimization method is characterized by comprising the following steps:
acquiring a predicted angle parameter and a predicted meteorological parameter;
inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result;
adjusting the photovoltaic module according to the predicted output result;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
2. The photovoltaic tracking optimization method according to claim 1, wherein the photovoltaic tracking optimization model is a logistic regression model.
3. The method according to claim 1, wherein the adjusting the photovoltaic module according to the predicted output result specifically comprises:
when the predicted output result is a first result, adjusting the photovoltaic module to rotate to a fixed installation position;
and when the predicted output result is a second result, tracking the photovoltaic module according to a preset program.
4. The photovoltaic tracking optimization method according to claim 3, wherein:
when the photovoltaic tracking system is used for double-axis tracking, the fixed installation position is the optimal inclination angle of the installation place;
when the photovoltaic tracking system is in flat single-axis tracking, the fixed installation position is horizontal installation;
when the photovoltaic tracking system is used for tracking the inclined single shaft, the fixed installation position is the optimal inclination angle of the installation place.
5. The photovoltaic tracking optimization method according to claim 1, wherein the training of the photovoltaic tracking optimization model comprises the following steps:
acquiring a plurality of groups of training samples, wherein each group of training samples comprises input parameters and output parameters, the input parameters comprise meteorological parameters and angle parameters, and the output parameters comprise comparison results of power generation benefits of the photovoltaic modules fixedly installed under the conditions of the meteorological parameters and the angle parameters and power generation benefits of the tracking photovoltaic modules;
training a photovoltaic tracking optimization model according to the training sample to obtain a trained photovoltaic tracking optimization model; the comparison result of the power generation benefit of the fixedly installed photovoltaic module and the power generation benefit of the tracking photovoltaic module is as follows: and when the power generation benefit of the fixedly installed photovoltaic module is greater than or equal to the power generation benefit of the tracking photovoltaic module, recording the comparison result as a first result, and when the power generation benefit of the fixedly installed photovoltaic module is less than the power generation benefit of the tracking photovoltaic module, recording the comparison result as a second result.
6. The photovoltaic tracking optimization method according to claim 5, wherein the angle parameter, the meteorological parameter, the predicted angle parameter and the predicted meteorological parameter are normalized.
7. The photovoltaic tracking optimization method according to claim 5, wherein the power generation benefit of the tracking photovoltaic module is a difference between the total power generation amount of the tracking photovoltaic module and the power consumption amount consumed by the tracking photovoltaic module for tracking.
8. A photovoltaic tracking optimization apparatus, comprising:
the processor is used for acquiring a predicted angle parameter and a predicted meteorological parameter, inputting the predicted meteorological parameter and the predicted angle parameter into a trained photovoltaic tracking optimization model, acquiring a predicted output result, and adjusting the photovoltaic module according to the predicted output result;
the photovoltaic module is used for converting solar energy into electric energy;
the supporting shaft seat is used for controlling the orientation of the photovoltaic module according to the output of the processor;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
9. A photovoltaic tracking optimization system, comprising:
the acquisition module is used for acquiring the predicted angle parameter and the predicted meteorological parameter;
the processing module is used for inputting the predicted meteorological parameters and the predicted angle parameters into a trained photovoltaic tracking optimization model to obtain a predicted output result;
the execution module is used for adjusting the photovoltaic module according to the prediction output result;
the angle parameters comprise a solar hour angle, a solar altitude angle and a solar azimuth angle, and the meteorological parameters comprise temperature, humidity and wind speed.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method for photovoltaic tracking optimization according to any one of claims 1 to 7.
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