CN116721356A - Output power prediction method of photovoltaic system and related equipment - Google Patents
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Abstract
The invention provides an output power prediction method of a photovoltaic system and related equipment, and relates to the technical field of new energy. The method comprises the following steps: acquiring a plurality of environmental information of a target area corresponding to a photovoltaic system, wherein each environmental information corresponds to different modes respectively; acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information; determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent; and inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system. According to the invention, the output power of the photovoltaic system is predicted through various environmental information, so that the accuracy and reliability of a prediction result can be improved.
Description
Technical Field
The invention relates to the technical field of new energy, in particular to an output power prediction method of a photovoltaic system and related equipment.
Background
The output power of the photovoltaic power station has the characteristics of high randomness, volatility, intermittence and the like, and large-scale access to the power grid can bring serious challenges to the safe and stable operation and the electric energy quality of the power grid, so that the prediction of the output power of the photovoltaic power station has great significance for the reliable access to the power grid. The existing photovoltaic power station output power prediction method predicts illumination intensity as analysis data, and the analysis data is single in type, so that the reliability and accuracy of a prediction result are low.
Disclosure of Invention
The invention provides an output power prediction method of a photovoltaic system and related equipment, which are used for solving the defects that in the prior art, the output power prediction method of a photovoltaic power station predicts illumination intensity as analysis data, and the analysis data is single in type, so that the reliability and the accuracy of a prediction result are lower.
The invention provides a method for predicting output power of a photovoltaic system, which comprises the following steps:
acquiring a plurality of environmental information of a target area corresponding to a photovoltaic system, wherein each environmental information corresponds to different modes respectively;
acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
and inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
According to the output power prediction method of the photovoltaic system provided by the invention, the semantic information corresponding to each environmental information is obtained according to each semantic template, and the method comprises the following steps:
acquiring characteristic information corresponding to the environment information aiming at each piece of environment information;
and filling a plurality of filling areas in the semantic template of the environment information according to the characteristic information to obtain the semantic information, wherein each filling area corresponds to different basic information types.
According to the output power prediction method of the photovoltaic system provided by the invention, the recoding data corresponding to each piece of environment information is determined according to the semantic information of each piece of environment information, and the method comprises the following steps:
for each piece of environment information, a mapping table and filling content corresponding to each filling area in the semantic information of the environment information are obtained, wherein the mapping table comprises a plurality of standard filling contents and codes corresponding to each standard filling content;
determining target codes corresponding to each filling area according to the mapping table and the filling content of each filling area;
and determining the recoded data corresponding to the environment information according to each target code.
According to the output power prediction method of the photovoltaic system provided by the invention, the target codes corresponding to the filling areas are determined according to the mapping table and the filling content of the filling areas, and the method comprises the following steps:
for each filling area, obtaining the similarity between the filling content corresponding to the filling area and each standard filling content corresponding to the filling area;
determining target standard filling content according to the similarity corresponding to each standard filling content;
and determining the target code corresponding to the filling area according to the code corresponding to the target standard filling content.
According to the output power prediction method of the photovoltaic system provided by the invention, the plurality of environmental information comprises at least two of sky image data, environmental temperature data and air quality indexes.
According to the output power prediction method of the photovoltaic system provided by the invention, the target prediction model is an attention model, and the recoding data are input into the target prediction model to obtain the corresponding predicted output power of the photovoltaic system, and the method comprises the following steps:
determining the environmental state of the target area according to the environmental information, and determining weight labels corresponding to the recoded data according to the environmental state;
splicing the recoded data containing the weight labels to obtain weight recoded data;
and inputting the weight coded data into the target prediction model to obtain the predicted output power.
According to the output power prediction method of the photovoltaic system provided by the invention, the environmental state of the target area is determined according to the environmental information, and the method comprises the following steps:
acquiring characteristic information corresponding to each environmental information;
and inputting the characteristic information into a state classification model to obtain the environment state.
The invention also provides an output power prediction device of the photovoltaic system, which comprises:
the data acquisition module is used for acquiring a plurality of environmental information of a target area corresponding to the photovoltaic system, wherein the environmental information respectively corresponds to different modes;
the semantic acquisition module is used for acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of the environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
the data coding module is used for determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
and the power prediction module is used for inputting the recoding data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the output power prediction method of the photovoltaic system according to any one of the above when executing the computer program.
The invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of predicting output power of a photovoltaic system as described in any one of the above.
According to the output power prediction method and the related equipment of the photovoltaic system, the plurality of environmental information of the target area corresponding to the photovoltaic system are obtained, wherein the environmental information respectively corresponds to different modes; acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information; determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent; and inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system. According to the invention, the output power of the photovoltaic system is predicted through various environmental information, so that the accuracy and reliability of a prediction result can be improved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for predicting output power of a photovoltaic system according to the present invention;
fig. 2 is a schematic structural diagram of an output power prediction device of a photovoltaic system provided by the invention;
fig. 3 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A method for predicting output power of a photovoltaic system according to the present invention is described below with reference to fig. 1, and includes the steps of:
s100, acquiring a plurality of environmental information of a target area corresponding to a photovoltaic system, wherein each environmental information corresponds to different modes;
s200, acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
s300, determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
s400, inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
In particular, the photovoltaic system is a new energy system capable of automatically generating electric energy based on solar radiation and illumination, so that the operation of the photovoltaic system is highly dependent on the environmental conditions of the region where the photovoltaic system is located. Each region in this embodiment where the photovoltaic system is disposed may be a target region. Environmental information of multiple modes, such as environmental temperature, environmental air quality, sky images, etc., can be acquired in the target area to reflect environmental conditions in the target area. In the embodiment, a target prediction model is pre-constructed, the input of the target prediction model is multi-mode environment information, and the output is the predicted output power of the photovoltaic system. In order to realize fusion of various environmental information, for each environmental information, extracting semantic information of the environmental information through a semantic template corresponding to the environmental information. And then recoding is carried out according to the semantic information to obtain recoded data of the environment information, so that the modes of the environment information are unified. And finally, inputting each recoded data into a target prediction model which is trained in advance, wherein the target prediction model is trained by a large amount of training data, and a complex mapping relation between input and output is learned, so that the output power of the photovoltaic system in the current environment can be automatically predicted based on each recoded data input, and the predicted output power is obtained. According to the embodiment, the output power of the photovoltaic system is predicted through the environmental information of a plurality of different modes, so that the accuracy and the reliability of a prediction result can be improved.
For example, assume that the plurality of environmental information includes sky images, temperature data, wind sound audio of the target area. Extracting semantic information of the sky image into multi-cloud-quantity-uniform cloud distribution-deep blue sky color through a semantic template of the sky image, and determining recoded data 1 according to the semantic information; extracting semantic information of temperature data to be high temperature through a semantic template of the temperature data, and determining recoded data 2 according to the semantic information; extracting semantic information of the sky image into strong wind power-high wind speed through a semantic template of wind sound audio, and determining recoded data 3 according to the semantic information. And then inputting the recoded data 1, 2 and 3 into a target prediction model to obtain the predicted output power of the photovoltaic system of 1 kilowatt.
In one implementation manner, the obtaining, according to each semantic template, semantic information corresponding to each environmental information includes:
acquiring characteristic information corresponding to the environment information aiming at each piece of environment information;
and filling a plurality of filling areas in the semantic template of the environment information according to the characteristic information to obtain the semantic information, wherein each filling area corresponds to different basic information types.
Specifically, in this embodiment, for the environmental information of each modality, the corresponding semantic template is set in advance. The semantic template comprises a plurality of filling areas, and each filling area corresponds to an important basic information category of the environment information. After the environmental information is obtained, the environmental information is subjected to feature extraction to obtain the feature information of the environmental information. And then filling each filling area in the semantic template one by one based on the characteristic information to obtain the semantic information of the environment information. According to the embodiment, important semantic information of the environment information can be extracted rapidly in a template filling mode, the information quantity can be simplified while the integrity of the information is ensured, and the reliability of a subsequent prediction result and the processing efficiency of a target prediction model are improved.
For example, assume that the plurality of environmental information includes sky images, temperature data, wind sound audio of the target area. The filling bits are represented in the semantic templates [ in ]. The semantic template of the sky image is cloud quantity, cloud distribution, sky color, extracted semantic information is cloud quantity, even sky color, and recoded data 1 is determined according to the semantic information; the semantic template of the temperature data is the temperature, the extracted semantic information is the temperature, and recoding data 2 is determined according to the semantic information; the semantic template of the wind sound audio is wind power, the extracted semantic information is wind power, and the extracted semantic information is high wind speed.
In one implementation manner, the determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information includes:
for each piece of environment information, a mapping table and filling content corresponding to each filling area in the semantic information of the environment information are obtained, wherein the mapping table comprises a plurality of standard filling contents and codes corresponding to each standard filling content;
determining target codes corresponding to each filling area according to the mapping table and the filling content of each filling area;
and determining the recoded data corresponding to the environment information according to each target code.
Specifically, in order to implement fast encoding, in this embodiment, a mapping table corresponding to each filling area is set in advance for each filling area, where the mapping table is used to reflect a plurality of preset standard filling contents and respective corresponding encodings, and the filling contents corresponding to the filling area are compared with the mapping table, so that a target encoding corresponding to the filling contents can be fast determined.
For example, the mapping table of the filling area corresponding to the cloud amount is shown in the following table 1, the mapping table of the filling area corresponding to the cloud distribution is shown in the following table 2, and the mapping table of the filling area corresponding to the sky color is shown in the following table 3.
TABLE 1 mapping table of filling area corresponding to cloud cover
。
TABLE 2 mapping table of filling area corresponding to cloud distribution
。
TABLE 3 mapping table of filling area corresponding to sky color
。
If the semantic information extracted from the sky image is the cloud quantity of more than one, the cloud distribution of even, the sky color of deep blue, the target code of the cloud quantity of more than one is determined to be 3 according to the table 1, according to the method, the target code of the [ even ] cloud distribution is determined to be 01 according to the table 2, the target code of the [ deep blue ] sky color is determined to be 003 according to the table 3, and the recoded data corresponding to the sky image is 3-01-003.
In one implementation manner, the determining, according to the mapping table and the padding content of each padding area, the target code corresponding to each padding area includes:
for each filling area, obtaining the similarity between the filling content corresponding to the filling area and each standard filling content corresponding to the filling area;
determining target standard filling content according to the similarity corresponding to each standard filling content;
and determining the target code corresponding to the filling area according to the code corresponding to the target standard filling content.
Specifically, in the comparison process of the filling content and the mapping table in this embodiment, the similarity between the filling content and each standard filling content in the mapping table is actually calculated, and finally, the standard filling content with the highest similarity is used as the matching object corresponding to the current filling content. And determining the target code corresponding to the current filling content through the code of the matching object in the mapping table. According to the embodiment, the codes corresponding to the filling content can be rapidly determined in a similarity calculation mode, and the coding efficiency is improved.
In one implementation, the environmental information includes an image of the sky, temperature data, and wind sound audio.
Specifically, because the information such as the quantity and the distribution condition of the cloud cover can influence the efficiency and the yield of the photovoltaic system, and the sky image can intuitively reflect the information related to the cloud cover, the sky image is taken as the environment information of one mode in the embodiment. Secondly, the photovoltaic efficiency is greatly influenced by the ambient temperature, the output power of the photovoltaic system is reduced due to the fact that the air temperature is too high, and the generated energy is also reduced, so that the temperature data is used as the environmental information of one mode in the embodiment. In addition, wind energy also affects the temperature of the photovoltaic system. Generally, the surface temperature of the photovoltaic system is higher than that of the ambient air, and wind cools the photovoltaic system, so that the efficiency and yield of the photovoltaic system in a warm environment are improved, and therefore the wind sound audio is taken as the environmental information of one mode in the embodiment.
In one implementation, the target prediction model is an attention model, and inputting each recoded data into the target prediction model to obtain a predicted output power corresponding to the photovoltaic system, including:
determining the environmental state of the target area according to the environmental information, and determining weight labels corresponding to the recoded data according to the environmental state;
splicing the recoded data containing the weight labels to obtain weight recoded data;
and inputting the weight coded data into the target prediction model to obtain the predicted output power.
Specifically, the photovoltaic efficiency is affected by various factors, and the influence degree of each influence factor on the output power of the photovoltaic system is different in different environment states, so that when the output power is predicted, the current environment state needs to be judged first, then the influence degree of each environment information on the predicted result is determined, and further different weight labels are given to each environment information, so that the accuracy of the predicted result is improved. For example, in a high-temperature environment state, the influence of temperature on the photovoltaic efficiency is obviously larger than other influencing factors, and the weight of temperature data is obviously larger than that of environment information of other modes; in the strong wind environment state, the influence of wind speed/wind power on the photovoltaic efficiency is obviously larger than other influencing factors, and the weight of wind sound audio frequency is obviously larger than that of environment information of other modes. And splicing the recoded data containing the weight labels to obtain the weight recoded data. And finally, inputting the model into a target prediction model constructed by adopting the attention model. The target prediction model can give different attention degrees according to the weights of different coded data, so that more attention degrees are put on the coded data with higher importance degree, and finally, the prediction output power with high reliability and high accuracy is output.
In one implementation, the determining the environmental state of the target area according to each environmental information includes:
acquiring characteristic information corresponding to each environmental information;
and inputting the characteristic information into a state classification model to obtain the environment state.
Specifically, in this embodiment, a state classification model is trained in advance, input data of the state classification model is characteristic information of multi-mode environmental information, and output data is a current environmental state. Because the state classification model is trained by a large amount of training data and a complex mapping relation between input and output is already learned, the current environment state can be accurately judged based on the input multi-mode environment information. The embodiment combines the deep learning technology and the environment information, and can rapidly and accurately judge the current environment state.
The output power prediction device of the photovoltaic system provided by the invention is described below, and the output power prediction device of the photovoltaic system described below and the output power prediction method of the photovoltaic system described above can be referred to correspondingly.
As shown in fig. 2, the apparatus includes:
the data acquisition module 210 is configured to acquire a plurality of environmental information of a target area corresponding to the photovoltaic system, where each environmental information corresponds to a different mode;
the semantic acquisition module 220 is configured to acquire semantic templates of the environmental information, and acquire semantic information corresponding to the environmental information according to the semantic templates, where the semantic template of each environmental information is used to reflect multiple basic information categories corresponding to the environmental information;
a data encoding module 230, configured to determine recoded data corresponding to each piece of environmental information according to the semantic information of each piece of environmental information, where a data format of each piece of recoded data is consistent;
and the power prediction module 240 is configured to input each recoded data into a target prediction model to obtain a predicted output power corresponding to the photovoltaic system.
Fig. 3 illustrates a physical schematic diagram of an electronic device, as shown in fig. 3, where the electronic device may include: processor 310, communication interface (Communications Interface) 320, memory 330 and communication bus 340, wherein processor 310, communication interface 320, memory 330 accomplish communication with each other through communication bus 340. The processor 310 may invoke logic instructions in the memory 330 to perform a method of output power prediction of a photovoltaic system, the method comprising: acquiring a plurality of environmental information of a target area corresponding to a photovoltaic system, wherein each environmental information corresponds to different modes respectively;
acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
and inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
Further, the logic instructions in the memory 330 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising a plurality of instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method of predicting output power of a photovoltaic system provided by the above methods, the method comprising: acquiring a plurality of environmental information of a target area corresponding to a photovoltaic system, wherein each environmental information corresponds to different modes respectively;
acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
and inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including a plurality of instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for predicting output power of a photovoltaic system, comprising:
acquiring a plurality of environmental information of a target area corresponding to a photovoltaic system, wherein each environmental information corresponds to different modes respectively;
acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of each environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
and inputting each recoded data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
2. The method for predicting output power of a photovoltaic system according to claim 1, wherein the obtaining semantic information corresponding to each environmental information according to each semantic template includes:
acquiring characteristic information corresponding to the environment information aiming at each piece of environment information;
and filling a plurality of filling areas in the semantic template of the environment information according to the characteristic information to obtain the semantic information, wherein each filling area corresponds to different basic information types.
3. The method for predicting output power of a photovoltaic system according to claim 2, wherein determining recoded data respectively corresponding to each of the environmental information according to the semantic information of each of the environmental information comprises:
for each piece of environment information, a mapping table and filling content corresponding to each filling area in the semantic information of the environment information are obtained, wherein the mapping table comprises a plurality of standard filling contents and codes corresponding to each standard filling content;
determining target codes corresponding to each filling area according to the mapping table and the filling content of each filling area;
and determining the recoded data corresponding to the environment information according to each target code.
4. The method for predicting output power of a photovoltaic system according to claim 3, wherein determining the target codes respectively corresponding to the filling areas according to the mapping table and the filling content of each filling area comprises:
for each filling area, obtaining the similarity between the filling content corresponding to the filling area and each standard filling content corresponding to the filling area;
determining target standard filling content according to the similarity corresponding to each standard filling content;
and determining the target code corresponding to the filling area according to the code corresponding to the target standard filling content.
5. The method of claim 1, wherein the plurality of environmental information includes at least two of sky image data, ambient temperature data, and an air quality index.
6. The method for predicting output power of a photovoltaic system according to claim 1, wherein the target prediction model is an attention model, and the inputting each recoded data into the target prediction model to obtain the predicted output power corresponding to the photovoltaic system comprises:
determining the environmental state of the target area according to the environmental information, and determining weight labels corresponding to the recoded data according to the environmental state;
splicing the recoded data containing the weight labels to obtain weight recoded data;
and inputting the weight coded data into the target prediction model to obtain the predicted output power.
7. The method of claim 6, wherein determining the environmental status of the target area from each of the environmental information comprises:
acquiring characteristic information corresponding to each environmental information;
and inputting the characteristic information into a state classification model to obtain the environment state.
8. An output power prediction apparatus for a photovoltaic system, comprising:
the data acquisition module is used for acquiring a plurality of environmental information of a target area corresponding to the photovoltaic system, wherein the environmental information respectively corresponds to different modes;
the semantic acquisition module is used for acquiring semantic templates of the environment information, and acquiring semantic information corresponding to the environment information according to the semantic templates, wherein the semantic templates of the environment information are used for reflecting a plurality of basic information categories corresponding to the environment information;
the data coding module is used for determining recoded data corresponding to each piece of environment information according to the semantic information of each piece of environment information, wherein the data format of each piece of recoded data is consistent;
and the power prediction module is used for inputting the recoding data into a target prediction model to obtain the predicted output power corresponding to the photovoltaic system.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of predicting the output power of a photovoltaic system according to any one of claims 1 to 7 when executing the computer program.
10. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the output power prediction method of a photovoltaic system according to any one of claims 1 to 7.
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