Method, system and medium for calculating power generation of perovskite assembly

Abstract

The application discloses a method and system for calculating power generation of a perovskite component and a medium, and belongs to the technical field of photovoltaic power generation. The method comprises the following steps: acquiring the actual solar radiation intensity of the perovskite component during work, the cleaning interval days, the operation years, the installation angle of the photovoltaic panel and the ground, and the maximum power of the perovskite component under standard test conditions; using the actual solar radiation intensity of the perovskite component during work, the cleaning interval days, the operation years, the installation angle of the photovoltaic panel and the ground, and the maximum power of the perovskite component under standard test conditions; and calculating the maximum power point power generation of the perovskite photovoltaic component during daily work. The method can adapt to the characteristics of the perovskite component and realize high-precision calculation of power generation.

Description

Technical Field

[0001] This disclosure pertains to the field of photovoltaic power generation technology, and particularly relates to a method, system, and medium for calculating the power generation of a perovskite module. Background Technology

[0002] Perovskite photovoltaic modules have become an important development direction in the field of photovoltaic technology due to their high efficiency and low cost manufacturing potential, but their power generation prediction has special necessity for system design and operation and maintenance.

[0003] Perovskite modules exhibit significant stability defects, with rapid light-induced degradation and sensitive thermal degradation, far exceeding the aging rate of silicon-based modules. If their power output cannot be accurately predicted, it will lead to a lag in power plant operation and maintenance strategies and accelerate module performance degradation. At the same time, their environmental response characteristics are more complex and highly sensitive to the environment. This strong environmental sensitivity directly affects the matching efficiency between the power plant and the inverter, as well as the accuracy of power dispatching. Therefore, there is an urgent need for targeted power prediction methods to support system design.

[0004] Existing power generation prediction technologies are mainly developed for silicon-based modules and are difficult to adapt to the characteristics of perovskite modules, thus having obvious shortcomings. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a method, system, and medium for calculating the power generation of perovskite modules. By utilizing actual solar irradiance, cleaning interval days, years of operation, installation angle, and standard test power, combined with factors such as temperature, contamination, aging, and system-wide correction factors, the actual power generation of perovskite modules can be accurately calculated.

[0006] The following is the technical content of this disclosure: A method for calculating the power generation of a perovskite module, comprising: Obtain the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and maximum power of the perovskite module under standard test conditions when it is in operation; Using the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and maximum power of the perovskite photovoltaic module under standard test conditions during operation, the maximum power point power generation of the perovskite photovoltaic module during daily operation is calculated; the formula is:

[0007] in, This represents the maximum power point output of the perovskite photovoltaic module during daily operation. , d represents the cleaning interval in days, and t represents the number of years the perovskite module has been in operation. The installation angle between the photovoltaic panel and the ground is given by A, where A is the overall system correction factor, and TKP is the power temperature coefficient. This represents the maximum power of the perovskite module under standard test conditions.

[0008] Furthermore, The actual solar irradiance intensity is obtained as follows: Real-time illumination data of the perovskite module during its working hours from sunrise to sunset is collected at preset time intervals by using an irradiation sensor installed on or near the module surface.

[0009] Furthermore, The calculation of the system's overall correction coefficient is as follows:

[0010] in, The wiring resistance loss coefficient of the photovoltaic system. The inverter conversion efficiency coefficient. This is the electrical matching loss coefficient between components.

[0011] Furthermore, The power temperature coefficient TKP is a factory-calibrated parameter of the perovskite module, or obtained through a standard temperature gradient test experiment, and is used to characterize the change in module power when the ambient temperature changes by 1°C.

[0012] Furthermore, Before calculating power generation, the following is also included: The actual solar irradiance collected is preprocessed; the preprocessing includes outlier data removal, missing value completion, data smoothing, and parameter standardization.

[0013] Furthermore, The abnormal data removal is as follows: data with solar irradiance ≤ 0 and ambient temperature exceeding the normal operating temperature range of the perovskite module are deleted. The missing value completion method uses linear interpolation or polynomial interpolation. The data smoothing process involves using a 5-minute moving average method to process the solar irradiance.

[0014] Furthermore, When the cleaning interval d ≤ 15 days, the contamination correction factor The value is 1; When d > 15 days .

[0015] A power generation calculation system for a perovskite module, comprising: The data acquisition module is used to acquire the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel and the ground, and the maximum power of the perovskite module under standard test conditions when the perovskite module is in operation. The calculation module is used to calculate the maximum power point output of the perovskite photovoltaic module during daily operation, using the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and the maximum power of the perovskite module under standard test conditions. The formula is as follows:

[0016] in, This represents the maximum power point output of the perovskite photovoltaic module during daily operation. , d represents the cleaning interval in days, and t represents the number of years the perovskite module has been in operation. The installation angle between the photovoltaic panel and the ground is given by A, where A is the overall system correction factor, and TKP is the power temperature coefficient. This represents the maximum power of the perovskite module under standard test conditions.

[0017] Furthermore, The calculation of the system's overall correction coefficient is as follows: ; in, The wiring resistance loss coefficient of the photovoltaic system. The inverter conversion efficiency coefficient. This is the electrical matching loss coefficient between components.

[0018] A computer storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method described thereon.

[0019] Compared with the prior art, this application has the following advantages: By obtaining the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and maximum power of the perovskite photovoltaic module under standard test conditions, and by combining these parameters with formulas that include pollution correction factors, aging correction factors, power temperature coefficient, installation angle correction term, and system comprehensive correction coefficient, the maximum power point power generation of the perovskite photovoltaic module during daily operation is calculated. This method accurately adapts the characteristics of the perovskite module and quantifies its actual power generation. Since the above parameters and correction factors are specifically designed for the characteristics of perovskite modules, such as rapid light decay, susceptibility to high temperatures, rapid aging, easy contamination, and environmental sensitivity, they can accurately calculate the impact of contamination, aging, temperature, installation angle, and system losses on power generation. This makes up for the shortcomings of existing calculation methods that are only suitable for silicon-based modules and not compatible with perovskite modules, thus solving the technical problem of inaccurate prediction of power generation of perovskite modules.

[0020] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A schematic diagram of the method of this disclosure is shown. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] like Figure 1 A schematic diagram of the method according to the present invention is shown. Specific implementation details of the present invention include: Step 1: Collect data, including: Environmental parameter acquisition: Focus on the module's operating period (sunrise to sunset) and collect solar irradiance (IRR) hourly; the solar irradiance must cover the actual amount of irradiance received by the module's light-receiving surface; Component inherent parameter acquisition: Extract the maximum power under standard test conditions from the component's factory inspection report. This parameter is the benchmark for calculating the actual power. At the same time, obtain the component's power temperature coefficient. This coefficient needs to match the perovskite module's heat-induced degradation sensitive characteristics and is directly related to the impact of temperature on power output. Installation and operation parameter collection: On-site measurement of the installation angle between the photovoltaic panel and the ground to ensure that the measurement accuracy meets the calculation requirements; Record the number of days between the last cleaning of the module and the calculation date, which is used to quantify the impact of pollution on power; Calculate the cumulative number of years of operation from the module commissioning date, accurate to 0.1 years, to reflect the power degradation caused by long-term aging of the module; System correction parameter determination: Based on the actual configuration of the perovskite photovoltaic system, the system comprehensive correction coefficient is determined. This coefficient needs to take into account non-component factors such as wiring resistance loss, inverter conversion efficiency, and inter-component matching loss in the system. It is derived through actual testing or industry standard parameters to ensure that it can accurately reflect the power loss at the system level.

[0025] Step 2: Data preprocessing, including: Abnormal data removal: Filter and delete abnormal data that does not conform to actual operating conditions, including data with solar irradiance ≤0 during non-nighttime periods and data with ambient temperature exceeding the normal operating range of perovskite modules; if the percentage of abnormal data in a single day exceeds 0%, valid data for the same time period on adjacent dates should be added as a reference to avoid abnormal data affecting the calculation results.

[0026] Missing value completion: For occasional missing data such as solar irradiance and ambient temperature, the completion method is selected based on the distribution of valid data around the missing data. If there are only two valid data points adjacent to the missing data, linear interpolation is used for completion; if there are three or more valid data points adjacent to the missing data, polynomial interpolation is used for completion to ensure the continuity of the data sequence.

[0027] Data smoothing: Since solar irradiance is easily affected by factors such as cloud shadows and instantaneous strong light, resulting in high-frequency fluctuations, a 5-minute moving average method is used to process it. By sliding the calculation of the average irradiance within adjacent 5 minutes, short-term fluctuation interference is eliminated, and stable hourly effective irradiance data is obtained, which is more in line with the stable irradiance conditions actually received by the module.

[0028] Parameter standardization: unify the units and formats of all collected parameters to make them compatible with the requirements of the power calculation formula; for example, convert the photovoltaic panel installation angle into a standard angle value and the cumulative operating years of the module into a value in years to avoid calculation errors caused by inconsistent units or incorrect formats.

[0029] Step 3: Calculate the daily power generation model formula for the perovskite module using the preprocessed data. The calculation formula is as follows:

[0030] in, This represents the maximum power point output of the perovskite photovoltaic module during daily operation. , =1-0.005t, where d is the cleaning interval in days and t is the number of years of operation. Let A be the installation angle between the photovoltaic panel and the ground, and let A be the overall system correction factor. For power temperature coefficient, This represents the maximum power of the component under standard test conditions.

[0031] The system comprehensive correction coefficient is calculated as follows: ; in, The wiring resistance loss coefficient of the photovoltaic system. The inverter conversion efficiency coefficient. This is the electrical matching loss coefficient between components.

[0032] Among them, the power temperature coefficient TKP is a factory-calibrated parameter of the perovskite module, or obtained through a standard temperature gradient test experiment, and is used to characterize the change in module power when the ambient temperature changes by 1°C.

[0033] Among them, when the cleaning interval d ≤ 15 days, the contamination correction factor The value is 1; When d > 15 days .

[0034] Technical effects: 1) Precisely matching perovskite characteristics to significantly improve prediction accuracy: Addressing the characteristics of perovskite modules, such as rapid light-induced degradation, sensitivity to thermal degradation, and significant impact from contamination, a method is introduced... (Pollution Correction) (Aging correction) and dedicated TKP (Temperature correction) reduce the power prediction deviation from more than 15% to less than 5% compared to traditional silicon-based module power prediction methods, thus closely matching the actual output of the module.

[0035] 2) Directly guide power plant operation and maintenance decisions: based on It can quantify pollution power loss, helping to determine reasonable cleaning cycles; through It can predict aging trends and avoid excessive component aging that leads to a decrease in system efficiency.

[0036] 3) Supporting the optimized design of perovskite systems: The system comprehensive correction coefficient A can accurately match the actual losses of different power plants, providing data support for inverter selection (which needs to match the predicted power) and system capacity design (to avoid power waste or insufficiency), and reducing system design risks.

[0037] The core principle of this publicly disclosed formula is: This formula uses the maximum power (P_STC_MPP) of perovskite modules under standard test conditions as a benchmark. It quantifies the difference between actual and standard operating conditions layer by layer through multi-dimensional correction factors, specifically addressing the stability defects and environmental sensitivity characteristics of perovskite modules. In the IRR term, sin(α) reflects the effective coefficient of the photovoltaic panel installation angle on irradiance reception. Combined with the actual solar irradiance (IRR), it can correct the deviation between standard and actual irradiance. The power temperature coefficient (TKP) quantifies the power when the ambient temperature deviates from the standard temperature. To address the sensitivity of perovskite modules to thermal degradation, the pollution correction factor is calculated based on the number of days between cleaning intervals, focusing on power degradation caused by short-term pollution. The aging correction factor is calculated based on the cumulative number of years of operation, adapting to the faster long-term aging rate of perovskite modules compared to silicon-based modules. The system comprehensive correction coefficient integrates system-level losses such as wiring resistance loss, inverter conversion efficiency, and inter-module matching loss. Ultimately, through the coordinated calculation of these correction factors and benchmark parameters, the maximum power point generation of perovskite modules during actual operation is accurately calculated, ensuring that the results closely reflect actual engineering scenarios.

[0038] Based on the above method, this disclosure also provides a system corresponding to the above method, which includes: The data acquisition module is used to acquire the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel and the ground, and the maximum power of the perovskite module under standard test conditions when the perovskite module is in operation. The calculation module is used to calculate the maximum power point output of the perovskite photovoltaic module during daily operation, using the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and the maximum power of the perovskite module under standard test conditions. The formula is as follows:

[0039] in, This represents the maximum power point output of the perovskite photovoltaic module during daily operation. , d represents the cleaning interval in days, and t represents the number of years the perovskite module has been in operation. The installation angle between the photovoltaic panel and the ground is given by A, where A is the overall system correction factor, and TKP is the power temperature coefficient. This represents the maximum power of the perovskite module under standard test conditions.

[0040] Based on the same inventive concept, this disclosure also provides a computer storage medium having executable instructions stored thereon, which are executed by a processor to cause the processor to implement the above-described method.

[0041] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for calculating the power generation of a perovskite module, characterized in that, include: Obtain the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and maximum power of the perovskite module under standard test conditions when it is in operation; Using the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and maximum power of the perovskite photovoltaic module under standard test conditions during operation, the maximum power point power generation of the perovskite photovoltaic module during daily operation is calculated; the formula is: in, This represents the maximum power point output of the perovskite photovoltaic module during daily operation. , d represents the cleaning interval in days, and t represents the number of years the perovskite module has been in operation. The installation angle between the photovoltaic panel and the ground is given by A, where A is the overall system correction factor, and TKP is the power temperature coefficient. This represents the maximum power of the perovskite module under standard test conditions.

2. The method for calculating the power generation of a perovskite module according to claim 1, characterized in that, The actual solar irradiance intensity is obtained as follows: Real-time illumination data of the perovskite module during its working hours from sunrise to sunset is collected at preset time intervals by using an irradiation sensor installed on or near the module surface.

3. The method for calculating the power generation of a perovskite module according to claim 1, characterized in that, The calculation of the system's overall correction coefficient is as follows: in, The wiring resistance loss coefficient of the photovoltaic system. The inverter conversion efficiency coefficient. This is the electrical matching loss coefficient between components.

4. The method for calculating the power generation of a perovskite module according to claim 1, characterized in that, The power temperature coefficient TKP is a factory-calibrated parameter of the perovskite module, or obtained through a standard temperature gradient test experiment, and is used to characterize the change in module power when the ambient temperature changes by 1°C.

5. The method for calculating the power generation of a perovskite module according to claim 1, characterized in that, Before calculating power generation, the following is also included: The actual solar irradiance collected is preprocessed; the preprocessing includes outlier removal, missing value completion, data smoothing, and parameter standardization.

6. The method for calculating the power generation of a perovskite module according to claim 5, characterized in that, The abnormal data removal is as follows: data with solar irradiance ≤ 0 and ambient temperature exceeding the normal operating temperature range of perovskite modules are deleted. The missing value completion method uses linear interpolation or polynomial interpolation. The data smoothing process involves using a 5-minute moving average method to process the solar irradiance.

7. The method for calculating the power generation of a perovskite module according to claim 1, characterized in that, When the cleaning interval d ≤ 15 days, the contamination correction factor The value is 1; When d > 15 days .

8. A power generation calculation system for a perovskite module, characterized in that, include: The data acquisition module is used to acquire the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel and the ground, and the maximum power of the perovskite module under standard test conditions when the perovskite module is in operation. The calculation module is used to calculate the maximum power point output of the perovskite photovoltaic module during daily operation, using the actual solar irradiance, cleaning interval days, operating years, installation angle of the photovoltaic panel to the ground, and the maximum power of the perovskite module under standard test conditions. The formula is as follows: in, This represents the maximum power point output of the perovskite photovoltaic module during daily operation. , d represents the cleaning interval in days, and t represents the number of years the perovskite module has been in operation. The installation angle between the photovoltaic panel and the ground is given by A, where A is the overall system correction factor, and TKP is the power temperature coefficient. This represents the maximum power of the perovskite module under standard test conditions.

9. The system according to claim 1, characterized in that, The calculation of the system's overall correction coefficient is as follows: ； in, The wiring resistance loss coefficient of the photovoltaic system. The inverter conversion efficiency coefficient. This is the electrical matching loss coefficient between components.

10. A computer storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 7.

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