CN114679133A - Photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction - Google Patents
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Abstract
The invention provides a photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction, wherein photovoltaic power generation basic data are collected and then subjected to large-area division and photovoltaic array setting, the generated energy of each large area in a preset time period is predicted, the actual power generation power of the photovoltaic array is obtained, and if the large area power generation in the photovoltaic array is abnormal, an abnormal position is judged until the abnormal power generation of a photovoltaic single plate is judged; application of the method to a computer-readable storage medium and a computer device. The method has the advantages that the judgment of the abnormal power generation of the photovoltaic array is more accurate, the photovoltaic single plate is easier to position, the damaged photovoltaic single plate can be timely processed, and the larger loss is avoided; the manual experience level requirement for material purchasing quantity judgment and the related data statistical time are reduced, the purchasing quantity is more accurate, and the inventory overstock is reduced; the manpower and material resources input for regular inspection is reduced, abnormal conditions are discovered more timely and accurately, and the safety of photovoltaic power generation is guaranteed.
Description
Technical Field
The invention relates to the technical field of electric digital data processing, in particular to a photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction in a photovoltaic ultra-short term.
Background
The photovoltaic power generation is a technology for directly converting light energy into electric energy by utilizing a photovoltaic effect of a semiconductor interface, solar cells (photovoltaic single plates) are connected in series and then are packaged and protected, a large-area solar cell module (photovoltaic array) can be formed, and then a power controller and other components are matched to form a photovoltaic power generation device.
In addition to other unstable factors of photovoltaic power generation, in the process of photovoltaic power generation, if a shelter exists on a photovoltaic panel, a fire disaster is easily caused due to uneven heating, and particularly in a scene of a photovoltaic array, the later effect is more serious, which causes damage to a large number of photovoltaic single plates one by one.
In the prior art, the traditional processing mode for the situation is discovered by manually and regularly patrolling and inspecting or by using an unmanned aerial vehicle patrolling and inspecting mode, so that a large amount of manpower and material resources are continuously invested for patrolling and inspecting, the cost is high, the inspection difficulty is large in fact, and a single board with problems is difficult to find at the first time; in addition, some technical schemes provide a scheme for finding abnormality by comparing different photovoltaic panel power generation differences, however, since different photovoltaic panels have different external factors, the power generation efficiency is different, and the problem of the photovoltaic array cannot be accurately found in the mode to a great extent.
Disclosure of Invention
The invention solves the problems in the prior art and provides an optimized photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction.
The invention adopts the technical scheme that a photovoltaic array abnormity judgment method based on power generation prediction comprises the following steps:
step 1: collecting basic data of photovoltaic power generation;
step 2: performing large-area division based on the photovoltaic power generation basic data and setting a photovoltaic array based on the divided large area;
and step 3: predicting the power generation amount of each large area in a preset time period;
and 4, step 4: obtaining actual generated power of the photovoltaic array;
and 5: if the large-area power generation in the photovoltaic array is abnormal, judging the abnormal position until the abnormal power generation of the photovoltaic single plate is judged; otherwise, repeat step 4.
Preferably, the basic data includes the generated power and the attenuation rate of each photovoltaic single board, and the illumination intensity and the weather of the location.
Preferably, based on the basic data of each photovoltaic single plate, the power generation influence factor is determined, and a theoretical dynamic distribution model is constructed.
Preferably, in step 2, based on the basic data of photovoltaic power generation, large areas within a preset range are divided, and the difference value of the basic data of photovoltaic power generation within the same large area is smaller than a threshold value; and setting the photovoltaic array in the large area based on the theoretical dynamic distribution model until the photovoltaic power generation of the large area reaches a predicted value.
Preferably, in the step 3, the short-term power generation amount of the photovoltaic single board is predicted by combining the theoretical dynamic distribution model according to the conditions of the same ratio and the ring ratio of the historical power generation.
Preferably, the short term is 24 hours.
Preferably, in the step 5, the abnormality is that a difference value between the actual power generation power of the photovoltaic array and the predicted value exceeds a threshold value, after the abnormal photovoltaic array is determined, information of other photovoltaic panels adjacent to each specified photovoltaic panel is traversed, group dispersion analysis is performed, and the photovoltaic panel with deviated power generation data is found out.
Preferably, if more than one photovoltaic single board has abnormal power generation capacity and the power generation capacities of all the photovoltaic single boards with abnormal power generation capacities are smaller than the expected value, the unmanned aerial vehicle is used for judging whether shielding exists and carrying out corresponding processing; if the power generation amount of only one photovoltaic single plate is abnormal, the problem is manually checked and correspondingly processed.
A computer-readable storage medium on which a photovoltaic array abnormality judgment program based on photovoltaic ultra-short term power generation prediction is stored, the program, when executed by a processor, implementing the photovoltaic array abnormality judgment method based on photovoltaic ultra-short term power generation prediction.
A computer device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the photovoltaic array abnormity judgment method based on photovoltaic ultra-short term power generation prediction is adopted.
The invention provides an optimized photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction.A large area division is carried out after photovoltaic power generation basic data is collected, a photovoltaic array is set based on the divided large area, the generated energy of each large area in a preset time period is predicted and the actual power generation power of the photovoltaic array is obtained, if the large area power generation in the photovoltaic array is abnormal, the abnormal position is judged until the abnormal power generation of a photovoltaic single plate is judged; the invention also implements the application of the method to computer-readable storage media and computer devices.
According to the method, the predicted power of the photovoltaic ultra-short-term power generation is compared with the actual power generation power, and the comparison of the power generation powers of other photovoltaic panels is combined, so that the abnormal power generation judgment of the photovoltaic array is more accurate, the photovoltaic single board is easier to position, the damaged photovoltaic single board can be timely processed, and the larger loss is avoided.
The invention reduces the requirement of human experience level for judging the purchase quantity of the material, reduces the statistical time of related data, makes the purchase quantity more accurate, and reduces the overstock of the stock on the basis of ensuring the requirement; the manpower and material resources input for regular inspection of the photovoltaic power generation panel is reduced, the abnormal condition of the power generation panel is discovered more timely and accurately, and the safety of photovoltaic power generation is guaranteed.
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FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The present invention is described in further detail with reference to the following examples, but the scope of the present invention is not limited thereto.
The invention relates to a photovoltaic array abnormity judgment method based on power generation prediction, which comprises the following steps:
step 1: collecting basic data of photovoltaic power generation;
the basic data comprise the power generation power and the attenuation rate of each photovoltaic single board, and the illumination intensity and the weather of the place.
And confirming the power generation influence factor of each photovoltaic single plate based on the basic data of each photovoltaic single plate, and constructing a theoretical dynamic distribution model.
In the invention, basic data of each photovoltaic single plate is collected and recorded, wherein the basic data includes but is not limited to power generation power and attenuation rate, local real-time illumination intensity, weather and other various information which influence photovoltaic power generation efficiency; where weather includes, but is not limited to, sunny/cloudy/rainy days, air temperature, etc.
According to the photovoltaic single-board power generation method and device, based on the basic data, the power generation influence factor of each photovoltaic single-board can be obtained through conversion, the power generation influence factor is in positive correlation with power generation power and attenuation rate, and meanwhile, the time-interval fluctuation exists based on the illumination intensity of the place and weather.
In the invention, a theoretical dynamic distribution model constructed based on the power generation influence factor corresponds to the length and the width of one photovoltaic single board by an X axis and a Z axis, corresponds to the power generation amount of one photovoltaic single board along with the time change or the illumination intensity change or the weather change by the Z axis, and is related to basic data.
In the invention, further, a theoretical dynamic distribution model constructed based on the power generation influence factor corresponds to the length and width of a photovoltaic array by an X axis and a Z axis, corresponds to the power generation amount of each photovoltaic single plate in the photovoltaic array along with the time change or the illumination intensity change or the weather change by the Z axis, and is connected by a curved surface, and the power generation amount is related to basic data.
In the invention, in a further step, a theoretical dynamic distribution model constructed based on the power generation influence factor corresponds to the length and the width of the photovoltaic array in a large area by an X axis and a Z axis, and corresponds to the power generation amount of each photovoltaic single plate of the photovoltaic array in the large area along with the time change or the illumination intensity change or the weather change by the Z axis, and the power generation amount is connected by a curved surface and is related to basic data.
In the present invention, in practical applications, there is a theoretical value of the power generation amount, and there is a fluctuation range up and down based on the theoretical value.
Step 2: performing large-area division based on the photovoltaic power generation basic data and setting a photovoltaic array based on the divided large area;
in the step 2, large areas within a preset range are divided based on the photovoltaic power generation basic data, and the difference value of the photovoltaic power generation basic data within the same large area is smaller than a threshold value; and setting the photovoltaic array in the large area based on the theoretical dynamic distribution model until the photovoltaic power generation of the large area reaches the expected value.
In the invention, the fact that the difference value of the photovoltaic power generation basic data in the same large area is smaller than the threshold means that the areas to which the similar power generation data points are merged in the local areas, so that after the large areas are divided, the generated energy of the photovoltaic single boards of the photovoltaic arrays arranged in each large area is basically consistent, and the monitoring and the control in the subsequent power generation process are ensured.
According to the invention, after the large areas are divided, a predicted value is set for the photovoltaic power generation amount of each large area, the photovoltaic array and the photovoltaic single plates in the photovoltaic array are set based on the predicted value, and the power generation amounts of the photovoltaic arrays in different periods and different service lives can be obtained approximately after the attenuation rates of the photovoltaic single plates are matched.
And 3, step 3: predicting the power generation capacity of each large area in a preset time period;
And in the step 3, the short-term power generation amount of the photovoltaic single board is predicted by combining the theoretical dynamic distribution model according to the conditions of the same ratio and the ring ratio of the historical power generation power.
The short term is 24 hours.
According to the invention, the theoretical power generation amount in the latest time period can be obtained according to the same ratio and ring ratio conditions of historical power generation, and the short-term power generation amount of each photovoltaic single plate or each photovoltaic array can be pre-judged by fully considering factors of weather and local real-time illumination intensity after the theoretical dynamic distribution model is combined.
In the invention, after the theoretical dynamic distribution model is complete, the predictive accuracy can reach within 24 hours.
And 4, step 4: obtaining actual generated power of the photovoltaic array;
and 5: if the large-area power generation in the photovoltaic array is abnormal, judging the abnormal position until the abnormal power generation of the photovoltaic single plate is judged; otherwise, repeat step 4.
In the step 5, the abnormality is that the difference value between the actual generated power of the photovoltaic array and the predicted value exceeds a threshold value, after the abnormal photovoltaic array is determined, traversing information of other photovoltaic panels adjacent to each specified photovoltaic panel, performing group dispersion analysis, and finding out the photovoltaic panel with deviated generated data.
If the generated energy of more than one photovoltaic single board is abnormal and the generated energy of all the photovoltaic single boards with abnormal generated energy is smaller than the expected value, judging whether shielding exists and carrying out corresponding processing by the unmanned aerial vehicle; if the power generation amount of only one photovoltaic single plate is abnormal, the problem is manually checked and correspondingly processed.
In the invention, generally, the generated power is detected by taking a photovoltaic array as a unit, when an abnormality exists, the photovoltaic array can be positioned, the theoretical generated energy of each photovoltaic single board is further deduced, group dispersion analysis is carried out by traversing other photovoltaic board information adjacent to each specified photovoltaic single board, at this moment, the generated energy of one or more photovoltaic single boards is obviously lower than a preset value (or higher than the preset value), and the positioning can be realized.
According to the invention, comprehensive judgment is carried out by combining the result of the comparison and analysis of the specified photovoltaic single board/photovoltaic array ultra-short-term power generation amount prediction and the actual power generation amount and the photovoltaic array power generation deviation point, so that the abnormal condition of photovoltaic power generation can be more accurately monitored.
A computer-readable storage medium on which a photovoltaic array abnormality judgment program based on photovoltaic ultra-short term power generation prediction is stored, the program, when executed by a processor, implementing the photovoltaic array abnormality judgment method based on photovoltaic ultra-short term power generation prediction.
In order to implement the embodiment, a computer-readable storage medium is provided, on which a photovoltaic array abnormality judgment program based on photovoltaic ultra-short term power generation prediction is stored, and when the program is executed by a processor, the method for judging the photovoltaic array abnormality based on photovoltaic ultra-short term power generation prediction is implemented, so that the problems that in the prior art, the photovoltaic power generation panel is subjected to regular inspection, manpower and material resources are more in investment, the inspection effect is poor, and further, the photovoltaic power generation panel is large in loss and low in power generation efficiency are mainly solved.
A computer device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the photovoltaic array abnormity judgment method based on photovoltaic ultra-short term power generation prediction is adopted.
In order to implement the above embodiments, the present invention further relates to a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for determining an abnormality of a photovoltaic array based on photovoltaic ultra-short term power generation prediction is provided.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A photovoltaic array abnormity judgment method based on power generation prediction is characterized by comprising the following steps: the method comprises the following steps:
Step 1: collecting basic data of photovoltaic power generation;
step 2: performing large-area division based on the photovoltaic power generation basic data and setting a photovoltaic array based on the divided large area;
and step 3: predicting the power generation capacity of each large area in a preset time period;
and 4, step 4: obtaining actual generated power of the photovoltaic array;
and 5: if the large-area power generation in the photovoltaic array is abnormal, judging the abnormal position until the abnormal power generation of the photovoltaic single plate is judged; otherwise, repeat step 4.
2. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 1, characterized in that: the basic data comprise the power generation power and the attenuation rate of each photovoltaic single board, and the illumination intensity and the weather of the place.
3. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 2, characterized in that: and confirming the power generation influence factor of each photovoltaic single plate based on the basic data of each photovoltaic single plate, and constructing a theoretical dynamic distribution model.
4. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 3, characterized in that: in the step 2, large areas within a preset range are divided based on the photovoltaic power generation basic data, and the difference value of the photovoltaic power generation basic data within the same large area is smaller than a threshold value; and setting the photovoltaic array in the large area based on the theoretical dynamic distribution model until the photovoltaic power generation of the large area reaches the expected value.
5. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 3 or 4, characterized in that: and in the step 3, the short-term power generation amount of the photovoltaic single board is predicted by combining the theoretical dynamic distribution model according to the conditions of the same ratio and the ring ratio of the historical power generation power.
6. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 5, characterized in that: the short term is 24 hours.
7. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 1, characterized in that: in the step 5, the abnormality is that the difference value between the actual generated power of the photovoltaic array and the predicted value exceeds a threshold value, after the abnormal photovoltaic array is determined, traversing information of other photovoltaic panels adjacent to each specified photovoltaic panel, performing group dispersion analysis, and finding out the photovoltaic panel with deviated generated data.
8. The photovoltaic array abnormality judgment method based on power generation prediction according to claim 7, characterized in that: if the generated energy of more than one photovoltaic single board is abnormal and the generated energy of all the photovoltaic single boards with abnormal generated energy is smaller than the expected value, judging whether shielding exists and carrying out corresponding processing by the unmanned aerial vehicle; if the power generation amount of only one photovoltaic single plate is abnormal, the problem is manually checked and correspondingly processed.
9. A computer-readable storage medium, on which a photovoltaic array abnormality judgment program based on power generation prediction is stored, which when executed by a processor, implements the photovoltaic array abnormality judgment method based on power generation prediction according to any one of claims 1 to 8.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program based on the method for determining abnormality of photovoltaic array based on power generation prediction according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210131098.9A CN114679133A (en) | 2022-02-13 | 2022-02-13 | Photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202210131098.9A CN114679133A (en) | 2022-02-13 | 2022-02-13 | Photovoltaic array abnormity judgment method, medium and equipment based on power generation prediction |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115409209A (en) * | 2022-08-19 | 2022-11-29 | 江苏方天电力技术有限公司 | Distributed photovoltaic panel abnormity detection method and device and storage medium |
| CN117114254A (en) * | 2023-10-25 | 2023-11-24 | 山东电力工程咨询院有限公司 | Power grid new energy abnormal data monitoring method and system |
| CN118040907A (en) * | 2024-04-11 | 2024-05-14 | 北京煜邦电力技术股份有限公司 | Electric quantity acquisition terminal based on light Fu Bianduan automatic control strategy |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115409209A (en) * | 2022-08-19 | 2022-11-29 | 江苏方天电力技术有限公司 | Distributed photovoltaic panel abnormity detection method and device and storage medium |
| CN117114254A (en) * | 2023-10-25 | 2023-11-24 | 山东电力工程咨询院有限公司 | Power grid new energy abnormal data monitoring method and system |
| CN117114254B (en) * | 2023-10-25 | 2024-03-19 | 山东电力工程咨询院有限公司 | Power grid new energy abnormal data monitoring method and system |
| CN118040907A (en) * | 2024-04-11 | 2024-05-14 | 北京煜邦电力技术股份有限公司 | Electric quantity acquisition terminal based on light Fu Bianduan automatic control strategy |
| CN118040907B (en) * | 2024-04-11 | 2024-06-11 | 北京煜邦电力技术股份有限公司 | Electric quantity acquisition terminal based on light Fu Bianduan automatic control strategy |
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