Method and system for evaluating power increase capacity of nano coating of photovoltaic power station

Abstract

The invention belongs to the technical field of photovoltaic power generation, and provides a method and a system for evaluating the increased power generation capacity of a nano coating of a photovoltaic power station. The method comprises the following steps: determining a group string equivalent utilization hour relation model of a reference group and a comparison group according to regression fitting between group string equivalent utilization hours of the reference group and the comparison group when no nano coating is added; according to the equivalent utilization hours of the string of the reference group after the nano coating is added, predicting the equivalent utilization hours of the string of the comparison group after the nano coating is added; aiming at each region of the photovoltaic power station, solving a difference value between a ratio of an actual value to a predicted value of equivalent utilization hours of a group string of a comparison group after the nano coating is additionally arranged in a preset time period and 1 to obtain an electric quantity increasing rate of each region after the nano coating is additionally arranged; and calculating the average generation increasing rate of the photovoltaic power station after the nano coating is added, and calculating the overall generation increasing rate of the photovoltaic power station after the nano coating is added by combining the average generation increasing rate with the total generation amount of the photovoltaic power station after the nano coating is added.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic power generation, and in particular relates to a method and system for evaluating the increased power generation of a nano-coating in a photovoltaic power station. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Applying nano coatings on photovoltaic modules can increase power generation. Evaluating the power generation increase of photovoltaic power station nano coatings is of great significance for the scheduling of subsequent power generation and the planning of photovoltaic power station nano coating coating. The prior art provides a photovoltaic power station reflective film power generation increase structure and its power generation increase test method, which can improve the overall power generation of photovoltaic power stations and increase the revenue of photovoltaic thermal power companies. However, only the power generation of photovoltaic power generation strings with reflective films installed and photovoltaic power generation strings without reflective films installed is calculated to illustrate the increase in power generation, and the increase in power generation of the entire photovoltaic site cannot be calculated. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for evaluating the increased power generation of nano-coatings in photovoltaic power stations, which can accurately estimate the increased power generation of nano-coatings in the entire photovoltaic power station.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A first aspect of the present invention provides a method for evaluating the increased power generation of a nano-coating in a photovoltaic power station.

[0007] In one or more embodiments, a method for evaluating the increased power generation of a photovoltaic power station nano-coating is provided, comprising:

[0008] Determine the reference group and comparison group of the photovoltaic power station;

[0009] Obtain the equivalent utilization hours of the strings in the reference group and the comparison group when no nano coating is added, and the equivalent utilization hours of the strings in the reference group after the nano coating is added;

[0010] According to the regression fitting between the equivalent utilization hours of the strings in the reference group and the comparison group without adding nano coating, the relationship model of the equivalent utilization hours of the strings in the reference group and the comparison group was determined;

[0011] According to the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group, the equivalent utilization hours of the strings of the reference group after the nano coating is added are used to predict the equivalent utilization hours of the strings of the comparison group after the nano coating is added;

[0012] For each area of ​​the photovoltaic power station, the ratio of the actual value of the equivalent utilization hours of the strings after the nano-coating is added to the comparison group within the preset time period to the predicted value is then subtracted from 1 to obtain the increase rate of electricity generation after the nano-coating is added in each area;

[0013] The average increase rate after adding nano-coating to the photovoltaic power station is calculated, and then combined with the total power generation of the photovoltaic power station after nano-coating, the overall increase in power generation after adding nano-coating to the photovoltaic power station is calculated.

[0014] As an implementation method, the relationship model of the equivalent utilization hours of the reference group and the comparison group is a univariate linear regression model.

[0015] As an implementation method, the overall increased power generation ΔP of a photovoltaic power station after adding a nano coating is: P is the total power generation of the photovoltaic power station after adding nano coating; Average increase in production after adding nano coating to photovoltaic power stations.

[0016] As an implementation method, in the process of determining the reference group of a photovoltaic power station, when the reference group is a photovoltaic power station above 5MW, the photovoltaic power station is divided into several areas according to the general layout diagram of the photovoltaic array, and the principle of selecting the reference group from each area is the same as the principle of selecting the reference group of a photovoltaic power station below 5MW.

[0017] As an implementation method, the selection principles for the PV power station participation group below 5MW are as follows:

[0018] Only one set of observation data of photovoltaic module strings is selected as the reference group data, and the remaining multiple sets of data are all comparison group data.

[0019] As an implementation method, in the process of selecting a reference group of photovoltaic power stations below 5MW, the monthly average equivalent utilization hours, quarterly average equivalent utilization hours and annual average equivalent utilization hours of each group of inverters / transformers and the entire power station are counted, and the group closest to the annual equivalent utilization hours average of the power station is selected from the annual equivalent utilization hours of each group of inverter / transformer data as the reference group.

[0020] As an implementation method, in the process of selecting a reference group of photovoltaic power stations below 5MW, if there are multiple groups with the average annual equivalent utilization hours of the power station, the inverter / substation group with the quarterly equivalent utilization hours closest to the quarterly equivalent utilization hours of the power station is selected as the reference group;

[0021] If there are still multiple groups of data, select the inverter / substation group whose monthly equivalent utilization hours are closest to the monthly equivalent utilization hours of the power station as the reference group.

[0022] A second aspect of the present invention provides a system for evaluating the increased power generation of nano-coatings in photovoltaic power stations.

[0023] In one or more embodiments, a photovoltaic power station nano-coating power generation evaluation system includes:

[0024] A reference group and comparison group determination module, which is used to determine the reference group and comparison group of the photovoltaic power station;

[0025] An equivalent utilization hours acquisition module, which is used to obtain the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added, and the equivalent utilization hours of the strings of the reference group after the nano coating is added;

[0026] A data relationship model building module, which is used to determine the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group based on the regression fitting between the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added;

[0027] The comparison group data prediction module is used to predict the equivalent utilization hours of the strings of the comparison group after the nano coating is added based on the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group, based on the equivalent utilization hours of the strings of the reference group after the nano coating is added;

[0028] The regional electricity generation rate calculation module is used to calculate the ratio of the actual value of the equivalent utilization hours of the strings after the nano-coating is added to the comparison group within a preset time period to the predicted value, and then calculate the difference with 1 to obtain the electricity generation rate after the nano-coating is added in each area of ​​the photovoltaic power station;

[0029] The overall increased power generation calculation module is used to calculate the average increased power generation rate after the photovoltaic power station is equipped with nano-coating, and then combine the total power generation of the photovoltaic power station after the nano-coating to calculate the overall increased power generation after the photovoltaic power station is equipped with nano-coating.

[0030] A third aspect of the present invention provides a computer-readable storage medium.

[0031] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the above-mentioned method for evaluating the increased power generation of a nano-coating in a photovoltaic power station.

[0032] A fourth aspect of the present invention provides an electronic device.

[0033] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the above-mentioned method for evaluating the increased power generation of nano-coatings in photovoltaic power stations are implemented.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention achieves a high correlation between the comparison group and the reference group by fitting the relationship model between the equivalent utilization hours of the strings of the reference group and the comparison group, improves the precision of subsequent calculations, and ensures the accuracy of subsequent calculations; then, the equivalent utilization hours of the strings of the reference group after the nano-coating is added are used to predict the equivalent utilization hours of the strings of the comparison group after the nano-coating is added, and then the increase rate of electricity generation in each area is calculated, and finally, combined with the total power generation of the photovoltaic power station after the nano-coating, the purpose of accurately estimating the overall increase in power generation after the photovoltaic power station is added with the nano-coating is achieved.

[0036] The present invention uses a univariate linear regression model to establish a reasonable mathematical model for the comparison group and the reference group, realizes the basic model for calculating the increased power generation, and ensures the accuracy of subsequent calculations; it also realizes the regional representation of the photovoltaic site through multiple groups of reference groups and comparison groups, and can reasonably calculate the increased power generation of the entire photovoltaic power station, providing a basis for the economic analysis of the site. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0038] Figure 1 It is a schematic flow chart of a method for evaluating the increased power generation of a photovoltaic power station nano-coating according to an embodiment of the present invention;

[0039] Figure 2 Schematic diagram of the structure of the photovoltaic power station nano-coating power generation evaluation system according to an embodiment of the present invention;

[0040] Figure 3 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0042] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0043] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0044] Figure 1 FIG. 1 is a flow chart of a method for evaluating the increased power generation of a photovoltaic power station nano-coating in an embodiment of the present invention. Figure 1 The method for evaluating the increased power generation of a photovoltaic power station nano-coating in the present embodiment shown may include:

[0045] S101: Determine a reference group and a comparison group of the photovoltaic power station.

[0046] In step S101, in the process of determining the reference group of a photovoltaic power station, when the reference group is a photovoltaic power station above 5MW, the photovoltaic power station is divided into several areas according to the general plan layout of the photovoltaic array, and the principle of selecting the reference group from each area is the same as the principle of selecting the reference group of a photovoltaic power station below 5MW.

[0047] Among them, the selection principles for the PV power station participation group below 5MW are:

[0048] Only one set of observation data of photovoltaic module strings is selected as the reference group data, and the remaining multiple sets of data are all comparison group data.

[0049] In the process of selecting the reference group of photovoltaic power stations below 5MW, the monthly average equivalent utilization hours, quarterly average equivalent utilization hours and annual average equivalent utilization hours of each group of inverters / transformers and the entire power station are calculated, and the group closest to the annual average equivalent utilization hours of the power station is selected from the annual equivalent utilization hours of each group of inverter / transformer data as the reference group.

[0050] When selecting the reference group of PV power stations below 5MW, if there are multiple groups with the same annual equivalent utilization hours as the average of the power station, the inverter / substation group with the quarterly equivalent utilization hours closest to the quarterly equivalent utilization hours of the power station shall be selected as the reference group;

[0051] If there are still multiple groups of data, select the inverter / substation group whose monthly equivalent utilization hours are closest to the monthly equivalent utilization hours of the power station as the reference group.

[0052] S102: Obtain the equivalent utilization hours of the strings of the reference group and the comparison group when the nano-coating is not added, and the equivalent utilization hours of the strings of the reference group after the nano-coating is added.

[0053] Before obtaining the photovoltaic array power generation data of the photovoltaic power station reference group and the photovoltaic power station comparison group, it also includes checking multiple sets of original data obtained by observation before and after the "inverter / box transformer" is equipped with nano-coating, judging their integrity and rationality, and checking whether there are unreasonable data or missing data, and then processing and organizing them into valid data.

[0054] Completeness check: a) Quantity: The number of data should be equal to the expected number of recorded data. b) Time sequence: The time sequence of the data should be consistent with the expected start and end time, and should be continuous in the middle.

[0055] Reasonableness test: a) Range test: check whether the range of observation data is reasonable; b) Correlation test, mainly the reasonable correlation of adjacent inverter data; c) Trend test, mainly the reasonable change trend of observation data.

[0056] The processing of unreasonable data and missing data includes:

[0057] a) After inspection, list all unreasonable data and missing data and the time when they occurred.

[0058] b) Re-judge the unreasonable data, select the valid data that conforms to the actual situation, and return to the original data group.

[0059] c) The data recorded by the spare or reference sensors in the same period will be analyzed and processed to replace the data that has been confirmed to be invalid or fill in the missing data.

[0060] d) After various tests, invalid data is eliminated and replaced with valid data, the measured data for at least one consecutive year is sorted out, and the electricity data is converted into equivalent utilization hours.

[0061] Among them, equivalent utilization hours = power generation (kwh) / rated capacity of photovoltaic array (kw).

[0062] S103: Determine the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group based on the regression fitting between the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added.

[0063] In this embodiment, the relationship model of the equivalent utilization hours of the reference group and the comparison group is a univariate linear regression model.

[0064] Assume that the equivalent utilization hours of the reference group without the nano coating is x 未涂 ; Equivalent utilization hours of the strings in the comparison group without the addition of nano coating y 未涂 ;x 未涂 With y 未涂 The fitting relationship between them is:

[0065] y 未涂 =a·x 未涂 +b;

[0066] Among them, a is the regression coefficient, b is a constant, and the least squares method is used to solve:

[0067]

[0068] in The subscript i is the average equivalent utilization hours of the strings in the reference group and the comparison group when no nano coating is added. The subscript i is the equivalent utilization hours of the i-th string; the total number of equivalent utilization hours of the strings in the preset time period.

[0069] According to y 未涂 =a·x 未涂 + b, we get Among them, x is the equivalent utilization hours of the string when the reference group adds nano coating; The predicted value of equivalent utilization hours of the strings when nano coating is added to the comparison group.

[0070] In order to verify the fitting degree of the mathematical model to the observed data, the determination coefficient R 2 As a judgment indicator:

[0071]

[0072] in The predicted value of equivalent utilization hours of the ith string when the nano coating is added to the comparison group; y i实际 The actual value of equivalent utilization hours of the ith string when the nano coating is added to the comparison group; The mean of equivalent utilization hours when nano coating is added to the control group; x i The measured value of equivalent utilization hours of the ith string when the reference group added nano-coating.

[0073] If the coefficient of determination R 2 ≥0.95, indicating that the data of the reference group and the comparison group have a strong fit and the mathematical model is basically established. Otherwise, the reference group and the comparison group should be reselected.

[0074] The present invention adopts the means of correlation test to solve the problem of rationality of correlation between the comparison group and the reference group, realizes high correlation between the comparison group and the reference group, and improves the accuracy of subsequent calculations.

[0075] S104: Based on the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group, the equivalent utilization hours of the strings of the reference group after the nano-coating is added are used to predict the equivalent utilization hours of the strings of the comparison group after the nano-coating is added.

[0076] S105: For each area of ​​the photovoltaic power station, the ratio of the actual value of the equivalent utilization hours of the strings after the nano coating is added to the comparison group within the preset time period to the predicted value is then subtracted from 1 to obtain the power generation increase rate k after the nano coating is added to each area: Wherein, n is the total number of equivalent utilization hours of the string within the preset time period.

[0077] S106: Calculate the average increase rate after the photovoltaic power station is equipped with nano coating, and then combine it with the total power generation of the photovoltaic power station after the nano coating to calculate the overall increase in power generation after the photovoltaic power station is equipped with nano coating.

[0078] When divided into N areas, the average increase rate of photovoltaic power stations after adding nano coating

[0079] The overall increase in power generation ΔP after adding nano coating to the photovoltaic power station is: P is the total power generation of the photovoltaic power station after adding nano coating; Average increase in production after adding nano coating to photovoltaic power stations.

[0080] Figure 2 Schematic diagram of a photovoltaic power station nano coating power generation evaluation system according to an embodiment of the present invention. Figure 1 The evaluation method of the increase in power generation of photovoltaic power station nano coatings corresponds to the following, Figure 2 As shown, the photovoltaic power station nano-coating power generation evaluation system in this embodiment may include:

[0081] A reference group and comparison group determination module 201, which is used to determine a reference group and a comparison group of a photovoltaic power station;

[0082] An equivalent utilization hours acquisition module 202 is used to acquire the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added, and the equivalent utilization hours of the strings of the reference group after the nano coating is added;

[0083] The data relationship model building module 203 is used to determine the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group according to the regression fitting between the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added;

[0084] The comparison group data prediction module 204 is used to predict the equivalent utilization hours of the strings of the comparison group after the nano coating is added based on the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group, based on the equivalent utilization hours of the strings of the reference group after the nano coating is added;

[0085] The regional power generation rate calculation module 205 is used to calculate the ratio of the actual value of the equivalent utilization hours of the strings after the nano-coating is added to the comparison group within a preset time period to the predicted value, and then calculate the difference with 1 to obtain the power generation rate after the nano-coating is added in each area of ​​the photovoltaic power station;

[0086] The overall increased power generation calculation module 206 is used to calculate the average increased power generation rate after the photovoltaic power station is equipped with nano coating, and then calculate the overall increased power generation after the photovoltaic power station is equipped with nano coating in combination with the total power generation after the photovoltaic power station is equipped with nano coating.

[0087] It should be noted here that Figure 2 The modules in the photovoltaic power station nano coating power generation evaluation system are Figure 1 The various steps in the photovoltaic power station nano-coating power generation increase evaluation method correspond one to one, and the specific implementation process is the same, which will not be repeated here.

[0088] Reference Figure 3 , a schematic diagram of an electronic device is given. It should be noted that, Figure 3 The electronic device 300 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0089] like Figure 3 As shown, electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage part 308 into a random access memory (RAM) 303. In RAM 303, various programs and data required for system operation are also stored. Central processing unit 301, ROM 302 and RAM 303 are connected to each other via a bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0090] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a local area network (LAN) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0091] When the central processing unit 301 in the electronic device of this embodiment executes the program, the following is achieved: Figure 1 The steps in the method for evaluating the increased power generation of nano-coatings in photovoltaic power plants are shown.

[0092] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer readable medium, the computer program including a computer program for executing Figure 1In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit 301, various functions defined in the apparatus of the present application are executed.

[0093] in, Figure 1 The computer program instructions corresponding to the method shown may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0094] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating the increased power generation of a photovoltaic power station nano-coating, characterized in that: include: Determine the reference group and comparison group of the photovoltaic power station; Obtain the equivalent utilization hours of the strings in the reference group and the comparison group when no nano coating is added, and the equivalent utilization hours of the strings in the reference group after the nano coating is added; According to the regression fitting between the equivalent utilization hours of the strings in the reference group and the comparison group without adding nano coating, the relationship model of the equivalent utilization hours of the strings in the reference group and the comparison group was determined; According to the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group, the equivalent utilization hours of the strings of the reference group after the nano coating is added are used to predict the equivalent utilization hours of the strings of the comparison group after the nano coating is added; For each area of ​​the photovoltaic power station, the ratio of the actual value of the equivalent utilization hours of the strings after the nano-coating is added to the comparison group within the preset time period to the predicted value is then subtracted from 1 to obtain the increase rate of electricity generation after the nano-coating is added in each area; The average increase rate after adding nano-coating to the photovoltaic power station is calculated, and then combined with the total power generation of the photovoltaic power station after nano-coating, the overall increase in power generation after adding nano-coating to the photovoltaic power station is calculated.

2. The method for evaluating the increased power generation of a photovoltaic power station nano-coating according to claim 1, characterized in that: The relationship model between the equivalent utilization hours of the reference group and the comparison group was a univariate linear regression model.

3. The method for evaluating the increased power generation of a photovoltaic power station nano-coating according to claim 1, characterized in that: The overall increase in power generation ΔP after adding nano coating to the photovoltaic power station is: P is the total power generation of the photovoltaic power station after adding nano coating; Average increase in production after adding nano coating to photovoltaic power stations.

4. The method for evaluating the increased power generation of a photovoltaic power station nano-coating according to claim 1, characterized in that: In the process of determining the participating group of a photovoltaic power station, when the participating group is a photovoltaic power station above 5MW, the photovoltaic power station is divided into several areas according to the general plan layout of the photovoltaic array, and the principle of selecting the participating group from each area is the same as the principle of selecting the participating group of a photovoltaic power station below 5MW.

5. The method for evaluating the increased power generation of a photovoltaic power station nano-coating according to claim 4, characterized in that: The selection principles for the PV power station participation group below 5MW are as follows: Only one set of observation data of photovoltaic module strings is selected as the reference group data, and the remaining sets of data are all comparison group data.

6. The method for evaluating the increased power generation of a photovoltaic power station nano-coating according to claim 4, characterized in that: In the process of selecting the reference group of photovoltaic power stations below 5MW, the monthly average equivalent utilization hours, quarterly average equivalent utilization hours and annual average equivalent utilization hours of each group of inverters / transformers and the entire power station are calculated, and the group closest to the annual average equivalent utilization hours of the power station is selected from the annual equivalent utilization hours of each group of inverter / transformer data as the reference group.

7. The method for evaluating the increased power generation of a photovoltaic power station nano-coating according to claim 4, characterized in that: When selecting the reference group of PV power stations below 5MW, if there are multiple groups with the same annual equivalent utilization hours as the average of the power station, the inverter / substation group with the quarterly equivalent utilization hours closest to the quarterly equivalent utilization hours of the power station shall be selected as the reference group; If there are still multiple groups of data, select the inverter / substation group whose monthly equivalent utilization hours are closest to the monthly equivalent utilization hours of the power station as the reference group.

8. A photovoltaic power station nano-coating power generation evaluation system, characterized in that: include: A reference group and comparison group determination module, which is used to determine the reference group and comparison group of the photovoltaic power station; An equivalent utilization hours acquisition module, which is used to obtain the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added, and the equivalent utilization hours of the strings of the reference group after the nano coating is added; A data relationship model building module, which is used to determine the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group based on the regression fitting between the equivalent utilization hours of the strings of the reference group and the comparison group when the nano coating is not added; The comparison group data prediction module is used to predict the equivalent utilization hours of the strings of the comparison group after the nano coating is added based on the relationship model of the equivalent utilization hours of the strings of the reference group and the comparison group, based on the equivalent utilization hours of the strings of the reference group after the nano coating is added; The regional electricity generation rate calculation module is used to calculate the ratio of the actual value of the equivalent utilization hours of the strings after the nano-coating is added to the comparison group within a preset time period to the predicted value, and then calculate the difference with 1 to obtain the electricity generation rate after the nano-coating is added in each area of ​​the photovoltaic power station; The overall increased power generation calculation module is used to calculate the average increased power generation rate after the photovoltaic power station is equipped with nano-coating, and then combine the total power generation of the photovoltaic power station after the nano-coating to calculate the overall increased power generation after the photovoltaic power station is equipped with nano-coating.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the method for evaluating the increased power generation of nano-coatings in a photovoltaic power station as described in any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the method for evaluating the increased power generation of nano-coatings in a photovoltaic power station as described in any one of claims 1 to 7 are implemented.

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