Method and device for loss analysis of a photovoltaic power plant

Abstract

The application discloses a kind of photovoltaic power station's loss analysis method and device, it is related to computer technical field.The specific embodiment of the method includes: in response to the loss analysis request of photovoltaic power station, weather data in specified period, installation data and inverter data of photovoltaic power station are acquired;Theoretical power generation, power generation under dirt and shadow power generation of photovoltaic power station are determined according to weather data, installation data and inverter data;The loss analysis of photovoltaic power station is carried out according to theoretical power generation, power generation under dirt and shadow power generation.The embodiment can be combined weather data in specified period, installation data and inverter data of photovoltaic power station to calculate theoretical power generation, power generation under dirt and shadow power generation, so as to accurately, real-time loss analysis of photovoltaic power station can be carried out, and the production efficiency of photovoltaic power station is improved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and apparatus for loss analysis of photovoltaic power plants. Background Technology

[0002] In existing photovoltaic (PV) operation and maintenance (O&M) scenarios, a monitoring system built by the inverter manufacturer is typically used to monitor power generation data and report it in real time. However, existing monitoring systems do not aggregate and analyze the power generation data, nor do they identify potential issues such as shading or contamination based on this analysis. Field personnel typically only investigate and resolve issues when a portion of the power plant experiences prolonged periods of inefficient power generation, by which time significant power loss has already occurred, and often the cause of the power loss is not documented after the solution is implemented. Therefore, existing PV O&M systems cannot accurately and in real-time analyze the losses in PV power plants. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method and apparatus for loss analysis of photovoltaic power plants, which can calculate theoretical power generation, power generation under pollution and power generation under shadow by combining weather data, photovoltaic power plant installation data and inverter data within a specified time period, thereby enabling accurate and real-time loss analysis of photovoltaic power plants and improving the production efficiency of photovoltaic power plants.

[0004] To achieve the above objectives, according to one aspect of the present invention, a loss analysis method for a photovoltaic power plant is provided, comprising: In response to a loss analysis request from a photovoltaic power plant, obtain weather data, photovoltaic power plant installation data, and inverter data for a specified time period; The theoretical power generation of the photovoltaic power station is determined based on the weather data, the installation data, and the inverter data. The effective irradiance and contamination rate of the photovoltaic power station are determined based on the weather data and the installation data. The irradiance under contamination is obtained based on the contamination rate and the effective irradiance. The power generation under contamination is determined based on the irradiance under contamination, the weather data, the installation data, and the inverter data. The shaded strings and the strings with the highest power generation are determined based on the inverter data. The shaded strings, the strings with the highest power generation, the weather data, the installation data, and the inverter data are used to determine the shaded power generation. The loss analysis of the photovoltaic power station is conducted based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shadow.

[0005] Optionally, determining the theoretical power generation of the photovoltaic power station based on the weather data, the installation data, and the inverter data includes: calculating the power generation of a single component based on a single diode model based on the weather data, the installation data, and the inverter data; and determining the theoretical power generation of the photovoltaic power station based on the circuit topology of the photovoltaic power station and the power generation of the single component.

[0006] Optionally, the circuit topology of the photovoltaic power station is calculated using the following formula: , ,in, The number of components connected in series in each path. The installed capacity of the photovoltaic power station is [missing information]. Rated power for each component, The number of paths connected in parallel to the inverter, This represents the number of additional components outside the array design.

[0007] Optionally, the weather data includes solar position, air viscosity, and particulate data, and the installation data includes the photovoltaic module installation tilt angle and photovoltaic module installation azimuth angle. Determining the effective irradiance and contamination rate of the photovoltaic power station based on the weather data and the installation data includes: calculating the effective irradiance actually participating in module power generation based on the photovoltaic module installation tilt angle, the photovoltaic module installation azimuth angle, and the solar position to obtain the effective irradiance of the photovoltaic power station; and determining the contamination rate of the photovoltaic power station based on the air viscosity, the particulate data, and the photovoltaic module installation tilt angle.

[0008] Optionally, the weather data also includes rainfall data; after determining the contamination rate of the photovoltaic power station, the method further includes: correcting the contamination rate using the rainfall data to correct the contamination rate where the rainfall data exceeds a set threshold to 0.

[0009] Optionally, determining the shaded strings and the highest-generating strings based on the inverter data includes: determining whether the inverter data includes module operating current data; in response to the inverter data including module operating current data, integrating the module operating current data to generate a module curve by simulating the volt-ampere curve of the photovoltaic unit, and determining the string shading situation by analyzing whether there are multiple peaks in the module curve, and determining the shaded strings and the highest-generating strings based on the string shading situation; in response to the inverter data not including module operating current data, obtaining branch current data based on the inverter data, and determining the string shading situation by analyzing whether the branch current data is normal, and determining the shaded strings and the highest-generating strings based on the string shading situation.

[0010] Optionally, determining the shaded strings and the strings with the highest power generation based on the string shading situation includes: in response to determining that string shading exists based on the string shading situation, determining the shaded strings and the strings with the highest power generation from the strings of the photovoltaic power station based on the current magnitude of each string.

[0011] Optionally, determining the shadow power generation based on the shadow string, the string with the highest power generation, the weather data, the installation data, and the inverter data includes: determining a first power generation of the shadow string and a second power generation of the string with the highest power generation based on the weather data, the installation data, and the inverter data; and determining the shadow power generation based on the first power generation and the second power generation.

[0012] Optionally, loss analysis of the photovoltaic power station is performed based on the theoretical power generation, the power generation under pollution, and the power generation under shadow, including: determining the pollution loss power generation and the pollution loss electricity ratio based on the theoretical power generation and the power generation under pollution; and determining the shadow loss power generation and the shadow loss electricity ratio based on the theoretical power generation and the power generation under shadow.

[0013] According to another aspect of the present invention, a loss analysis device for a photovoltaic power plant is provided, comprising: The data acquisition module is used to respond to the loss analysis request from the photovoltaic power station by acquiring weather data, photovoltaic power station installation data, and inverter data within a specified time period; The theoretical power generation determination module is used to determine the theoretical power generation of the photovoltaic power station based on the weather data, the installation data, and the inverter data. The module for determining the amount of electricity generated from contamination is used to determine the effective irradiance and contamination rate of the photovoltaic power station based on the weather data and the installation data, and to obtain the irradiance under contamination based on the contamination rate and the effective irradiance, and to determine the amount of electricity generated under contamination based on the irradiance under contamination, the weather data, the installation data and the inverter data. The shadow power generation determination module is used to determine the shaded string and the string with the highest power generation based on the inverter data, and to determine the shadow power generation based on the shaded string, the string with the highest power generation, the weather data, the installation data, and the inverter data. The power loss analysis module is used to perform loss analysis on the photovoltaic power station based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shadow.

[0014] According to another aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the loss analysis method for photovoltaic power plants provided in the embodiments of the present invention.

[0015] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the loss analysis method for photovoltaic power plants provided in the embodiments of the present invention.

[0016] According to another aspect of the present invention, a computer program product is provided, including a computer program that, when executed by a processor, implements the loss analysis method for photovoltaic power plants provided in the embodiments of the present invention.

[0017] One embodiment of the above invention has the following advantages or beneficial effects: In response to a loss analysis request from a photovoltaic power station, it acquires weather data, installation data, and inverter data for a specified time period; determines the theoretical power generation of the photovoltaic power station based on the weather data, installation data, and inverter data; determines the effective irradiance and contamination rate of the photovoltaic power station based on the weather data and installation data, and obtains the irradiance under contamination based on the contamination rate and effective irradiance; determines the power generation under contamination based on the irradiance under contamination, weather data, installation data, and inverter data; identifies the shaded strings and the strings with the highest power generation based on the inverter data; and determines the shadow power generation based on the shaded strings, the strings with the highest power generation, weather data, installation data, and inverter data. This technical solution for loss analysis of a photovoltaic power station based on theoretical power generation, power generation under contamination, and shadow power generation can combine weather data, photovoltaic power station installation data, and inverter data for a specified time period to calculate theoretical power generation, power generation under contamination, and shadow power generation, thereby enabling accurate and real-time loss analysis of the photovoltaic power station and improving the production efficiency of the photovoltaic power station.

[0018] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0019] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic diagram of the main steps of a loss analysis method for a photovoltaic power plant according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the implementation principle of the photovoltaic power plant loss analysis system according to an embodiment of the present invention; Figure 3This is a schematic diagram of the main modules of a loss analysis device for a photovoltaic power plant according to an embodiment of the present invention; Figure 4 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 5 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0020] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0021] It should be noted that the technical solutions disclosed in this invention, regarding the collection, updating, analysis, processing, use, transmission, and storage of user personal information, all comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0022] In the description of the embodiments of the present invention, the technical terms involved and their definitions are as follows: SDM (Single Diode Model): A single-diode model for photovoltaic modules; MPP (Max Power Point): Maximum power point; GHI (Global Horizontal Irradiance): Total global irradiance; DNI (Direct Normal Irradiance): Vertical irradiance intensity; DHI (Diffuse Horizontal Irradiance): Horizontal diffuse irradiance; Brentq: A method for finding the roots of an equation; in practice, it is one of the root-finding methods in the SciPy library. Newton: A method for finding roots based on random initial values, which is one of the root-finding methods in the SciPy library; SR (Soiling Ratio): Soiling ratio; HSU (Humboldt State University): The model was named after the school because the dirtiness rate was mainly calculated using the equation proposed in a paper from this school. TODS (Time Series Outlier Detection System): A time series data anomaly detection system used to detect data points in time series data that differ from most data in terms of distribution, frequency, sequence distance, and other attributes.

[0023] In existing technologies, the formulas used in the industry for calculating theoretical power generation are relatively simple and crude. The vast majority of theoretical power generation calculations are as follows: ; in, Total horizontal irradiance ( (peak hours) Irradiation under standard conditions ( ), The installed capacity of the modules (kWp) is given by K, which is the overall efficiency coefficient. K is a fixed value (e.g., 0.88) set manually based on experience, taking into account factors such as module type correction, azimuth correction, solar utilization, collector line loss, and surface contamination correction, to account for all potential losses. This method can only estimate approximate results with large datasets and wide time granularities (daily, weekly, monthly, quarterly, yearly, etc.), and the smaller the granularity, the greater the error. It is particularly prone to significant errors in hourly theoretical power estimations, which are more valuable for reference, and it lacks the ability to differentiate between different loss types.

[0024] To address the technical problems existing in the prior art, the loss analysis method for photovoltaic power plants of this invention can estimate the theoretical DC power generation (i.e., the power generation of the photovoltaic modules) based on weather factors such as irradiance and the electrical and physical parameters of the photovoltaic modules. This invention implements the calculation of the theoretical power generation of photovoltaic power plants based on the classic single-diode model. In the calculation process, the subjective parameter of the K coefficient, present in the prior art, is absent, ensuring the objectivity and accuracy of the power generation calculation. Furthermore, in this invention, the theoretical power generation is only used as a basic model; that is, it is a fundamental component applied to the calculation of other losses, but is not affected by the loss model itself. All types of losses are analyzed in the form of input or output parameters of this component, making it easier to decompose or integrate different loss types based on requirements.

[0025] In existing technologies, loss analysis that can be categorized into different loss types is mostly labeled analysis, meaning it's a "known answer" data analysis based on known labels such as shading status or contamination. In real-world scenarios, photovoltaic (PV) operation and maintenance (O&M) companies primarily rely on monitoring data (current, voltage, real-time power, etc.) and fault alarm information for maintenance dispatch and operation. They lack known information on shading status or contamination, and often don't record data on contamination or shading after maintenance. Therefore, the aforementioned loss analysis is not practically applicable. Furthermore, there is simulation-based loss analysis in the industry, which simulates power generation under shading conditions and given fixed coefficients for heat loss, contamination rate, and line loss, generating loss analysis reports of arbitrary length. However, the environments of power plants vary significantly across different regions, with substantial differences in contamination rates and shading conditions. It's difficult to quantify these losses using standardized contamination and shading conditions in reality. It's also impossible to simulate shading by environmental modeling across hundreds of thousands of power plants.

[0026] To address this technical problem, the photovoltaic power plant loss analysis method of this invention enables the calculation of various losses even with only weather data and real-time reported monitoring data. For example, in this invention, pollution analysis is achieved by simulating the pollution rate and adding it to the effective irradiance using PM2.5 and PM10 data from environmental data. Shading analysis is achieved by analyzing the string current and voltage from monitoring data, using the series-parallel principle and analyzing the physical changes in current under shading. This method effectively solves practical problems from cause to effect, rather than simply deriving causes from effects. Note that photovoltaic power plants have their own topology or wiring diagram, and string current refers to the current in each row of series-connected modules (i.e., solar panels).

[0027] In existing technologies, major inverter manufacturers in actual operation and maintenance systems retain photovoltaic matrix topology diagrams of power plants. However, this type of data cannot be used as structured data to calculate theoretical power generation (2*10 and 4*5 matrix structures will have the same total power value, but different line voltages). For example, the branch voltage of two lines in a 2*10 system will be twice that of four lines in a 4*5 system. This higher voltage, based on the current inverter model of the power plant, may lead to inefficient power generation (such as peak shaving). Without this type of data, it is impossible to accurately assess and calculate theoretical power generation, and it is impossible to determine whether there are losses due to unreasonable design.

[0028] To address this technical problem, the photovoltaic power plant loss analysis method of this invention enables the automatic generation of topology design structures. It achieves the ability to automatically allocate the number of rows and columns of the photovoltaic matrix based on the total number of modules by analyzing the voltage range of the inverter under normal operating conditions and the open-circuit voltage parameters of the modules. Furthermore, this invention also enables the automatic calculation of string currents in the event of missing string current data (in practical applications, some inverter manufacturers do not provide string current data), by automatically splitting the MPPT (Max Power Point Tracking) current (i.e., the current generated after integrating multiple string currents in the inverter).

[0029] In existing technologies, there is relatively little research on contamination analysis. Most methods rely on simulating contamination indices using fixed parameters in a laboratory setting. For example, a contamination index of X% / day is pre-set for each hour or day. X is often derived from the average power generation statistics of a power plant in a fixed environment over a year or more, such as average loss = (beginning-of-year power generation - end-of-year power generation) / year. However, these methods operate under specific conditions, requiring the elimination of obstructions and the absence of faults to calculate a relatively accurate coefficient. In reality, each power plant has complex conditions, making it difficult to establish one or more universally applicable X values. Simply setting this value renders the contamination analysis largely meaningless.

[0030] To address this technical problem, the photovoltaic power station loss analysis method of the present invention enables the assessment of power generation losses caused by dust accumulation and pollution in real-world scenarios through laboratory dirt index calculation, and on this basis, the ability to adjust the parameters of the physical model.

[0031] In existing technologies, the methodology for shading analysis in laboratories mostly involves simulating the current-voltage (IV-V) analysis of a photovoltaic (PV) panel under known contamination conditions, such as the area and shape of the contamination. This is done by simulating the IV-V and PV-V curves and identifying multiple MPP (Max Power Point) or abnormal stepped curves to determine the presence of shading. However, this method requires monitoring the real-time photocurrent of each panel (i.e., the current generated by the PV panel under real-time irradiance), simulating the IV and PV curves at each moment using time-series photocurrent data, and then making judgments based on the curves. But in actual power plant monitoring systems, it is often unnecessary to monitor the operation of PV panels, and collecting relevant operational data would not incur unnecessary costs. Therefore, this method is difficult to implement in actual power generation.

[0032] To address this technical problem, the present invention provides a loss analysis method for photovoltaic power plants, which implements an algorithm for determining shading conditions based on branch current data monitored by the inverter. Based on real-time string current or string current decomposed through MPPT current analysis, the shading condition is determined according to the series and parallel connection configuration and circuit principles of the power plant. This method does not require monitoring the current of individual circuit components; it only requires more readily available current data for each string.

[0033] Figure 1 This is a schematic diagram illustrating the main steps of a loss analysis method for a photovoltaic power plant according to an embodiment of the present invention. Figure 1 As shown, the loss analysis method for photovoltaic power plants in this embodiment of the invention mainly includes the following steps S101 to S105.

[0034] Step S101: In response to the loss analysis request from the photovoltaic power station, obtain weather data, photovoltaic power station installation data, and inverter data for a specified time period. According to an embodiment of the present invention, the specified time period can be, for example, the most recent ten minutes, the most recent hour, etc., and is not limited to a longer time period. That is, the loss analysis of the present invention can be performed at any time.

[0035] In embodiments of the present invention, the parameters to be considered when performing loss analysis of a photovoltaic power plant include weather data, installation data of the photovoltaic power plant, and inverter data.

[0036] The weather data includes, for example, irradiance data (which can be broken down into total irradiance (GHI), direct irradiance (DNI), and diffuse irradiance (DHI), ambient temperature, relative humidity, air pressure, wind speed, PM2.5 (suspended particulate matter with a diameter of 2.5 micrometers or less) and PM10 (inhalable particulate matter, usually referring to particulate matter with a diameter of less than 10 micrometers) and rainfall data, with the maximum particle size of the data being hourly.

[0037] Installation data for photovoltaic (PV) power plants includes, for example, the latitude and longitude of the power plant location, the installation tilt angle of the PV modules (e.g., solar panels), the installation azimuth angle of the PV modules, the PV module model, the cell type of the PV modules (monocrystalline, polycrystalline, etc.), the maximum power point voltage of the PV modules, the maximum power point current of the PV modules, the open-circuit voltage of the PV modules, the short-circuit current of the PV modules, the temperature coefficient of the short-circuit current, the temperature coefficient of the open-circuit voltage, the temperature coefficient of the power, the number of cells connected in series per string, the inverter model, the maximum DC input power of the inverter, the inverter operating efficiency, and the inverter's optimal efficiency, etc. Most of the above data consists of static module and inverter parameters, which can be obtained by consulting the technical specifications corresponding to the PV module and inverter models.

[0038] Inverter data includes, for example, the current, voltage, and power of each branch (string), as well as the total output power of the inverter. Since installation data originally requires the circuit topology of the strings and the inverter, but to avoid situations where maintenance providers cannot provide structured circuit topology data, this invention supports the function of automatically calculating the topology based on the number of inverter branches and the installed capacity of the power plant.

[0039] Step S102: Determine the theoretical power generation of the photovoltaic power station based on weather data, installation data, and inverter data. Here, theoretical power generation refers to the power generation without considering losses such as pollution losses and shading losses. In embodiments of the present invention, the theoretical power generation of the photovoltaic power station can be determined by a power generation calculation module.

[0040] According to one embodiment of the present invention, the theoretical power generation of the photovoltaic power station is determined based on the weather data, the installation data, and the inverter data. Specifically, this may include: calculating the power generation of a single component based on a single diode model based on the weather data, the installation data, and the inverter data; and determining the theoretical power generation of the photovoltaic power station based on the circuit topology of the photovoltaic power station and the power generation of the single component.

[0041] According to one embodiment of the present invention, the circuit topology of the photovoltaic power station is calculated and generated using the following formula: , ,in, The number of components connected in series in each path. The installed capacity of the photovoltaic power station is [missing information]. Rated power for each component, The number of paths connected in parallel to the inverter, This represents the number of additional components outside the array design.

[0042] In embodiments of the present invention, the theoretical power generation is mainly calculated using the classic single diode model (SDM), which requires five parameters. These five parameters are fed into the IV curve equation under the classic SDM model, and the current, voltage, and power at the maximum power point are solved using Brentq or Newton's algorithm.

[0043] The current, voltage, and power at the maximum power point mentioned above are for a single component. The power generation of the entire photovoltaic power station still needs to be calculated based on the actual circuit topology of the power station.

[0044] In the absence of a provided circuit topology, this invention calculates the circuit topology information using the following method: , ,in, The number of components connected in series in each path. The installed capacity of the photovoltaic power station is [missing information]. Rated power for each component, The number of paths connected in parallel to the inverter, This refers to the number of additional components beyond the square matrix design. Theoretically, a square matrix topology is preferred. If additional components are added to a rectangular matrix, they should be evenly distributed after existing strings. The logic for adding extra components prioritizes adding them to branches with relatively high branch currents. Here, a string refers to each row of circuit components connected in series; in this embodiment, the circuit component is a solar panel.

[0045] Step S103: Determine the effective irradiance and contamination rate of the photovoltaic power station based on weather data and installation data, and obtain the irradiance under contamination based on the contamination rate and effective irradiance. Determine the power generation under contamination based on the irradiance under contamination, weather data, installation data and inverter data.

[0046] According to one embodiment of the present invention, the weather data includes solar position, air viscosity, and particulate data, and the installation data includes the photovoltaic module installation tilt angle and the photovoltaic module installation azimuth angle. Determining the effective irradiance and contamination rate of the photovoltaic power station based on the weather data and the installation data specifically includes: calculating the effective irradiance actually involved in the module's power generation based on the photovoltaic module installation tilt angle, the photovoltaic module installation azimuth angle, and the solar position to obtain the effective irradiance of the photovoltaic power station; and determining the contamination rate of the photovoltaic power station based on the air viscosity, the particulate data, and the photovoltaic module installation tilt angle. In embodiments of the present invention, a contamination simulation model can be used to calculate the contamination rate of the photovoltaic power station.

[0047] Specifically, when calculating theoretical power generation, the effective irradiance actually involved in power generation is calculated based on the installation tilt angle and azimuth angle of the photovoltaic modules, as well as the sun's position in weather data. There are two main ways to determine the pollution rate: one is to define a fixed loss rate gradient based on actual conditions, with power generation decreasing as the loss rate increases; the other is to use the HSU model to calculate the pollution rate. The HSU model mainly considers factors such as laminar and turbulent resistance of particles of different sizes in the air, air viscosity, etc., and summarizes PM2.5 and PM2.5... 10-2.5 The settling velocities of the two types of particles (PM2.5 to PM10) are used to calculate the theoretical cumulative mass m on the inclined surface of the photovoltaic cell within the time interval. The approximate calculation is as follows: , , , , in, The settling or displacement velocity (m / s) of particles between PM2.5 and PM10, and particles within the PM2.5 range. These are the aerodynamic drag and quasi-laminar drag received by the particles, respectively. The calculation methods for these two drags will not be elaborated in this invention. Particle density (g / m³) for two PM ranges 3 This is equivalent to the PM2.5 and PM10-PM2.5 values ​​commonly used in weather data. t represents any time period. These are the installation tilt angle of the photovoltaic module, particle diameter (μm), and particle density (kg / m³). 3 ), gravitational acceleration (m / s²) 2 ), sliding correction factor, air viscosity (kg / (m*s); SR is the dirtiness rate, and erf is the error function. (settling velocity) and (Deposition velocity) refers to the settling velocity, which can be simply understood as being calculated using physical parameters. , Calculate ,calculate When using PM2.5 particle diameter, Then it is Similarly, using the particle diameter of PM10, Then it is (That is: the settling velocity of PM10).

[0048] In the implementation of this invention (Settlement velocity of particulate matter between PM2.5 and PM10) and The settling velocities of PM2.5 particles were set to constants of 0.0009 m / s and 0.004 m / s in the experiment, where m and w represent the accumulated mass over a period of time. This method allows for the objective calculation of the pollution rate of any number of power plants based on local air conditions, rather than setting a single empirical value. However, a key point of this calculation formula is that the settling velocity, coefficients 34.37, 0.17, and 0.8473 are constant values ​​summarized from laboratory experiments and may deviate from actual conditions. Therefore, this invention also adds a gradient descent algorithm to correct the above parameters based on application scenario data to obtain a more accurate pollution index.

[0049] According to another embodiment of the present invention, the weather data further includes rainfall data; after determining the contamination rate of the photovoltaic power station, the method further includes: correcting the contamination rate using the rainfall data to correct the contamination rate of rainfall data exceeding a set threshold to 0. After converting the cumulative mass m into the contamination rate SR, the model allows the final output contamination rate to be corrected using rainfall data. For example, when a threshold of 10mm rainfall is set, rainfall exceeding this threshold can be assumed to be sufficient to completely clean the contamination from the photovoltaic modules. Therefore, when the rainfall data exceeds 10mm, the contamination rate will automatically be corrected to 0.

[0050] In embodiments of the present invention, the power generation under contamination conditions is determined based on irradiance under contamination, weather data, installation data, and inverter data. Specifically, this includes replacing the irradiance in the weather data with the irradiance under contamination, and determining the power generation under contamination based on the replaced weather data, installation data, and inverter data. Here, the power generation calculation module is still required to calculate the power generation under contamination. That is, the power generation under contamination needs to be calculated jointly using both the contamination simulation model and the power generation calculation module.

[0051] Step S104: Determine the shaded string and the string with the highest power generation based on the inverter data, and determine the shaded power generation based on the shaded string, the string with the highest power generation, weather data, installation data, and inverter data.

[0052] According to one embodiment of the present invention, determining the shaded strings and the strings with the highest power generation based on the inverter data may specifically include: determining whether the inverter data includes module operating current data; in response to the inverter data including module operating current data, integrating the module operating current data to generate a module curve by simulating the volt-ampere curve of the photovoltaic unit, and determining the string shading situation by analyzing whether there are multiple peaks in the module curve, and determining the shaded strings and the strings with the highest power generation based on the string shading situation; in response to the inverter data not including module operating current data, obtaining branch current data based on the inverter data, determining the string shading situation by analyzing whether the branch current data is normal, and determining the shaded strings and the strings with the highest power generation based on the string shading situation. In embodiments of the present invention, shading power generation can be calculated using a shading analysis model, which includes two parts: volt-ampere curve analysis and inverter branch current analysis. When module operating current data can be extracted from inverter data, the photovoltaic unit's current-voltage curve is simulated, and the photovoltaic unit curve data (aligning series current, summing series voltage) is integrated to form the module curve. Finally, the presence of multiple peaks in the module curve is analyzed to determine the shading status of the string. When no current data during module operation is extracted, the shading status of the string is determined by analyzing whether the branch currents are normal. Normally, the currents of each branch should maintain similar current and fluctuation states. Abnormal fluctuation states can be identified using a Time Series Outlier Detection System (TODS). For example, for multiple branches with currents of 8.7A, 8.5A, 9.0A, and 1.7A respectively, there is clearly string shading, and the current of the shaded string is 1.7A.

[0053] According to one embodiment of the present invention, determining the shaded string and the string with the highest power generation based on the string shading situation includes: in response to determining that string shading exists based on the string shading situation, determining the shaded string and the string with the highest power generation from each string of the photovoltaic power station based on the current magnitude of each string.

[0054] According to an embodiment of the present invention, determining the shadow power generation based on the shadow string, the string with the highest power generation, the weather data, the installation data, and the inverter data includes: determining a first power generation of the shadow string and a second power generation of the string with the highest power generation based on the weather data, the installation data, and the inverter data; and determining the shadow power generation based on the first power generation and the second power generation. Specifically, the difference between the second power generation and the first power generation can be used as the shadow power generation.

[0055] Step S105: Conduct a loss analysis of the photovoltaic power plant based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shadow.

[0056] According to an embodiment of the present invention, loss analysis of the photovoltaic power station is performed based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shading conditions. Specifically, this may include: determining the pollution loss power generation and the pollution loss ratio based on the theoretical power generation and the power generation under pollution conditions; and determining the shading loss power generation and the shading loss ratio based on the theoretical power generation and the power generation under shading conditions. After determining the power generation under pollution and shading conditions, the corresponding power loss and loss ratio are calculated by comparing it with the theoretical power generation. Similarly, other losses such as line losses and fault losses can be obtained by comparing the statistically calculated power loss with the theoretical power generation to obtain the corresponding power loss and loss ratio. Line losses can be... (I represents current, R represents resistance) or calculate the value based on the circuit conditions.

[0057] Figure 2 This is a schematic diagram illustrating the implementation principle of the photovoltaic power plant loss analysis system according to an embodiment of the present invention. Figure 2 As shown in the embodiments of the present invention, the loss analysis system for photovoltaic power plants is mainly based on weather data, installation data, and inverter data for loss analysis. Specifically, the theoretical power generation can be calculated using a power generation calculation model based on weather data, installation data, and inverter data; the irradiance under pollution conditions can be calculated using a pollution simulation model based on weather data, and then combined with the power generation calculation model to calculate the power generation under pollution conditions; the shaded strings and the strings with the highest power generation can be determined using a shading analysis model based on inverter data, and then combined with the power generation calculation model to calculate the shading power generation. Finally, statistical analysis is performed based on the theoretical power generation, the power generation under pollution conditions, and the shading power generation to obtain the pollution loss power generation, the pollution loss power ratio, the shading loss power generation, the shading loss power ratio, and various losses such as line loss and fault loss.

[0058] Figure 3 This is a schematic diagram of the main modules of a loss analysis device for a photovoltaic power plant according to an embodiment of the present invention. Figure 3 As shown, the photovoltaic power station loss analysis device 300 of this embodiment mainly includes a data acquisition module 301, a theoretical power generation determination module 302, a pollution power generation determination module 303, a shading power generation determination module 304, and a power loss analysis module 305.

[0059] The data acquisition module 301 is used to respond to the loss analysis request of the photovoltaic power station and acquire weather data, photovoltaic power station installation data and inverter data within a specified time period; Theoretical power generation determination module 302 is used to determine the theoretical power generation of the photovoltaic power station based on the weather data, the installation data, and the inverter data; The dirty power generation determination module 303 is used to determine the effective irradiance and dirt rate of the photovoltaic power station based on the weather data and the installation data, and to obtain the irradiance under dirt based on the dirt rate and the effective irradiance, and to determine the power generation under dirt based on the irradiance under dirt, the weather data, the installation data and the inverter data; The shadow power generation determination module 304 is used to determine the shaded string and the string with the highest power generation based on the inverter data, and to determine the shadow power generation based on the shaded string, the string with the highest power generation, the weather data, the installation data and the inverter data; The power loss analysis module 305 is used to perform loss analysis of the photovoltaic power station based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shadow.

[0060] According to one embodiment of the present invention, the theoretical power generation determination module 302 can also be used to: calculate the power generation of a single component based on a single diode model according to the weather data, the installation data and the inverter data; and determine the theoretical power generation of the photovoltaic power station based on the circuit topology of the photovoltaic power station and the power generation of the single component.

[0061] According to another embodiment of the present invention, the circuit topology of the photovoltaic power station is calculated and generated using the following formula: , ,in, The number of components connected in series in each path. The installed capacity of the photovoltaic power station is [missing information]. Rated power for each component, The number of paths connected in parallel to the inverter, This represents the number of additional components outside the array design.

[0062] According to another embodiment of the present invention, the weather data includes solar position, air viscosity, and particulate data, and the installation data includes photovoltaic module installation tilt angle and photovoltaic module installation azimuth angle; the pollution power generation determination module 303 can also be used to: calculate the effective irradiance of the photovoltaic power station actually participating in the power generation of the photovoltaic module based on the photovoltaic module installation tilt angle, the photovoltaic module installation azimuth angle, and the solar position, thereby obtaining the effective irradiance of the photovoltaic power station; and determine the pollution rate of the photovoltaic power station based on the air viscosity, the particulate data, and the photovoltaic module installation tilt angle.

[0063] According to another embodiment of the present invention, the weather data further includes rainfall data; after determining the pollution rate of the photovoltaic power station, the pollution power generation determination module 303 can also be used to: correct the pollution rate using the rainfall data, so as to correct the pollution rate of the rainfall data exceeding a set threshold to 0.

[0064] According to another embodiment of the present invention, the shading power generation determination module 304 can also be used to: determine whether the inverter data includes module operating current data; in response to the inverter data including module operating current data, integrate the module operating current data to generate a module curve by simulating the volt-ampere curve of the photovoltaic unit, and determine the string shading situation by analyzing whether there are multiple peaks in the module curve, and determine the shaded string and the string with the highest power generation according to the string shading situation; in response to the inverter data not including module operating current data, obtain branch current data according to the inverter data, and determine the string shading situation by analyzing whether the branch current data is normal, and determine the shaded string and the string with the highest power generation according to the string shading situation.

[0065] According to another embodiment of the present invention, the shading power generation determination module 304 can also be used to: in response to determining that there is string shading based on the string shading situation, determine the shaded string and the string with the highest power generation from each string of the photovoltaic power station based on the current magnitude of each string.

[0066] According to another embodiment of the present invention, the shadow power generation determination module 304 can also be used to: determine the first power generation of the shadow string and the second power generation of the string with the highest power generation based on the weather data, the installation data and the inverter data; and determine the shadow power generation based on the first power generation and the second power generation.

[0067] According to another embodiment of the present invention, the power loss analysis module 305 can also be used to: determine the power loss due to pollution and the ratio of power loss due to pollution based on the theoretical power generation and the power generation under pollution conditions; and determine the power loss due to shadow and the ratio of power loss due to shadow based on the theoretical power generation and the shadow power generation.

[0068] According to the technical solution of the present invention, in response to a loss analysis request from a photovoltaic power station, weather data, installation data of the photovoltaic power station, and inverter data within a specified time period are obtained; the theoretical power generation of the photovoltaic power station is determined based on the weather data, installation data, and inverter data; the effective irradiance and contamination rate of the photovoltaic power station are determined based on the weather data and installation data, and the irradiance under contamination is obtained based on the contamination rate and effective irradiance; the power generation under contamination is determined based on the irradiance under contamination, weather data, installation data, and inverter data; the shaded strings and the strings with the highest power generation are determined based on the inverter data; and the shadow power generation is determined based on the shaded strings, the strings with the highest power generation, weather data, installation data, and inverter data. This technical solution for loss analysis of the photovoltaic power station based on the theoretical power generation, the power generation under contamination, and the shadow power generation can combine weather data, installation data, and inverter data within a specified time period to calculate the theoretical power generation, the power generation under contamination, and the shadow power generation, thereby enabling accurate and real-time loss analysis of the photovoltaic power station and improving the production efficiency of the photovoltaic power station.

[0069] Figure 4 An exemplary system architecture 400 is shown for a loss analysis method or device for a photovoltaic power plant to which embodiments of the present invention can be applied.

[0070] like Figure 4 As shown, system architecture 400 may include terminal devices 401, 402, and 403, a network 404, and a server 405. Network 404 serves as the medium for providing communication links between terminal devices 401, 402, and 403 and server 405. Network 404 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0071] Users can use terminal devices 401, 402, and 403 to interact with server 405 via network 404 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 401, 402, and 403, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0072] Terminal devices 401, 402, and 403 can be various electronic devices with displays that support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0073] Server 405 can be a server that provides various services, such as a back-end management server that supports shopping websites browsed by users using terminal devices 401, 402, and 403 (for example only). The backend management server can respond to received requests for loss analysis from photovoltaic (PV) power plants by acquiring weather data, PV power plant installation data, and inverter data for a specified time period; determining the theoretical power generation of the PV power plant based on the weather data, installation data, and inverter data; determining the effective irradiance and contamination rate of the PV power plant based on the weather data and installation data, and obtaining the irradiance under contamination based on the contamination rate and effective irradiance; determining the power generation under contamination based on the irradiance under contamination, the weather data, installation data, and inverter data; identifying the shaded strings and the strings with the highest power generation based on the inverter data; determining the shaded power generation based on the shaded strings, the strings with the highest power generation, the weather data, installation data, and inverter data; performing loss analysis on the PV power plant based on the theoretical power generation, the power generation under contamination, and the shaded power generation; and feeding back the processing results (e.g., loss analysis results – just an example) to the terminal device.

[0074] It should be noted that the loss analysis method for photovoltaic power plants provided in this embodiment of the invention is generally executed by server 405, and correspondingly, the loss analysis device for photovoltaic power plants is generally installed in server 405.

[0075] It should be understood that Figure 4 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0076] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a computer system 500 suitable for implementing terminal devices or servers of the present invention. Figure 5 The terminal device or server shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0077] like Figure 5As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 502 or programs loaded from storage section 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the system 500. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0078] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 510 as needed so that computer programs read from it can be installed into storage section 508 as needed.

[0079] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs the functions defined above in the system of this invention.

[0080] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0081] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0082] The units or modules described in the embodiments of the present invention can be implemented in software or hardware. The described units or modules can also be housed in a processor; for example, a processor can be described as including a data acquisition module, a theoretical power generation determination module, a pollution power generation determination module, a shading power generation determination module, and a power loss analysis module. The names of these units or modules do not necessarily limit the specific unit or module itself. For example, the data acquisition module can also be described as "a module for acquiring weather data, photovoltaic power station installation data, and inverter data within a specified time period in response to a loss analysis request from a photovoltaic power station."

[0083] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist alone and not assembled into the device. The aforementioned computer-readable medium carries one or more programs, which, when executed by a device, cause the device to include: in response to a loss analysis request from a photovoltaic power station, acquiring weather data, installation data of the photovoltaic power station, and inverter data for a specified time period; determining the theoretical power generation of the photovoltaic power station based on the weather data, the installation data, and the inverter data; determining the effective irradiance and contamination rate of the photovoltaic power station based on the weather data and the installation data, and obtaining the irradiance under contamination based on the contamination rate and the effective irradiance, and determining the power generation under contamination based on the irradiance under contamination, the weather data, the installation data, and the inverter data; determining the shaded strings and the strings with the highest power generation based on the inverter data, and determining the shaded power generation based on the shaded strings, the strings with the highest power generation, the weather data, the installation data, and the inverter data; and performing a loss analysis of the photovoltaic power station based on the theoretical power generation, the power generation under contamination, and the shaded power generation.

[0084] According to the technical solution of the present invention, in response to a loss analysis request from a photovoltaic power station, weather data, installation data of the photovoltaic power station, and inverter data within a specified time period are obtained; the theoretical power generation of the photovoltaic power station is determined based on the weather data, installation data, and inverter data; the effective irradiance and contamination rate of the photovoltaic power station are determined based on the weather data and installation data, and the irradiance under contamination is obtained based on the contamination rate and effective irradiance; the power generation under contamination is determined based on the irradiance under contamination, weather data, installation data, and inverter data; the shaded strings and the strings with the highest power generation are determined based on the inverter data; and the shadow power generation is determined based on the shaded strings, the strings with the highest power generation, weather data, installation data, and inverter data. This technical solution for loss analysis of the photovoltaic power station based on the theoretical power generation, the power generation under contamination, and the shadow power generation can combine weather data, installation data, and inverter data within a specified time period to calculate the theoretical power generation, the power generation under contamination, and the shadow power generation, thereby enabling accurate and real-time loss analysis of the photovoltaic power station and improving the production efficiency of the photovoltaic power station.

[0085] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A loss analysis method for a photovoltaic power plant, characterized in that, include: In response to a loss analysis request from a photovoltaic power plant, obtain weather data, photovoltaic power plant installation data, and inverter data for a specified time period; The theoretical power generation of the photovoltaic power station is determined based on the weather data, the installation data, and the inverter data. The effective irradiance and contamination rate of the photovoltaic power station are determined based on the weather data and the installation data. The irradiance under contamination is obtained based on the contamination rate and the effective irradiance. The power generation under contamination is determined based on the irradiance under contamination, the weather data, the installation data, and the inverter data. The shaded strings and the strings with the highest power generation are determined based on the inverter data. The shaded strings, the strings with the highest power generation, the weather data, the installation data, and the inverter data are used to determine the shaded power generation. The loss analysis of the photovoltaic power station is conducted based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shadow.

2. The method according to claim 1, characterized in that, The theoretical power generation of the photovoltaic power station is determined based on the weather data, the installation data, and the inverter data, including: Based on the weather data, the installation data, and the inverter data, the power generation of a single component is calculated using a single diode model. The theoretical power generation of the photovoltaic power station is determined based on the circuit topology of the photovoltaic power station and the power generation of the individual components.

3. The method according to claim 2, characterized in that, The circuit topology of the photovoltaic power station is calculated and generated using the following formula: ， ， in, The number of components connected in series in each path. The installed capacity of the photovoltaic power station is [missing information]. Rated power for each component, The number of paths connected in parallel to the inverter, This represents the number of additional components outside the array design.

4. The method according to claim 1, characterized in that, The weather data includes the sun's position, air viscosity, and particulate data; the installation data includes the photovoltaic module installation tilt angle and the photovoltaic module installation azimuth angle. The effective irradiance and contamination rate of the photovoltaic power station are determined based on the weather data and the installation data, including: The effective irradiance of the photovoltaic power station is obtained by calculating the actual effective irradiance of the photovoltaic module's power generation based on the photovoltaic module's installation tilt angle, the photovoltaic module's installation azimuth angle, and the sun's position. The contamination rate of the photovoltaic power station is determined based on the air viscosity, the particle data, and the installation tilt angle of the photovoltaic modules.

5. The method according to claim 4, characterized in that, The weather data also includes rainfall data; after determining the pollution rate of the photovoltaic power station, it also includes: The dirt rate is corrected using the rainfall data to reduce the dirt rate to 0 if the rainfall data exceeds a set threshold.

6. The method according to claim 1, characterized in that, Based on the inverter data, the shaded strings and the strings with the highest power generation are determined, including: Determine whether the inverter data includes component operating current data; In response to the inverter data including the module operating current data, the module operating current data is integrated to generate a module curve by simulating the volt-ampere curve of the photovoltaic unit. The string shading situation is determined by analyzing whether there are multiple peaks in the module curve, and the shaded string and the string with the highest power generation are determined according to the string shading situation. Since the inverter data does not include component operating current data, branch current data is obtained based on the inverter data, and the string shading situation is determined by analyzing whether the branch current data is normal. Based on the string shading situation, the shaded strings and the strings with the highest power generation are identified.

7. The method according to claim 6, characterized in that, Based on the string shading situation, the shaded strings and the strings with the highest power generation are identified, including: In response to determining the presence of string shading based on string shading conditions, the shaded string and the string with the highest power generation are identified from the strings of the photovoltaic power station based on the current magnitude of each string.

8. The method according to claim 7, characterized in that, The shadow power generation is determined based on the shadow string, the string with the highest power generation, the weather data, the installation data, and the inverter data, including: The first power generation of the shaded string and the second power generation of the string with the highest power generation are determined based on the weather data, the installation data, and the inverter data. The shadow power generation is determined based on the first power generation and the second power generation.

9. The method according to claim 1, characterized in that, A loss analysis of the photovoltaic power station is conducted based on the theoretical power generation, the power generation under pollution conditions, and the power generation in shadow, including: The pollution loss power generation and the pollution loss power ratio are determined based on the theoretical power generation and the power generation under pollution conditions. The ratio of shadow loss power generation to shadow loss electricity generation is determined based on the theoretical power generation and the shadow power generation.

10. A loss analysis device for a photovoltaic power station, characterized in that, include: The data acquisition module is used to respond to the loss analysis request from the photovoltaic power station by acquiring weather data, photovoltaic power station installation data, and inverter data within a specified time period; The theoretical power generation determination module is used to determine the theoretical power generation of the photovoltaic power station based on the weather data, the installation data, and the inverter data. The module for determining the amount of electricity generated from contamination is used to determine the effective irradiance and contamination rate of the photovoltaic power station based on the weather data and the installation data, and to obtain the irradiance under contamination based on the contamination rate and the effective irradiance, and to determine the amount of electricity generated under contamination based on the irradiance under contamination, the weather data, the installation data and the inverter data. The shadow power generation determination module is used to determine the shaded string and the string with the highest power generation based on the inverter data, and to determine the shadow power generation based on the shaded string, the string with the highest power generation, the weather data, the installation data, and the inverter data. The power loss analysis module is used to perform loss analysis on the photovoltaic power station based on the theoretical power generation, the power generation under pollution conditions, and the power generation under shadow.

11. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-9.

12. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-9.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-9.

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