Solar power generation operation monitoring method

Abstract

The invention provides a solar power generation operation monitoring method, and relates to the field of photovoltaic power generation monitoring, and the method comprises the steps: collecting the actual output power of a solar battery pack according to a time sequence in a preset period, and outputting a plurality of actual output power values in the period; monitoring a crystal structure in the solar battery pack at the beginning of each period, and determining a complete index of the crystal structure; acquiring environmental parameters corresponding to the time sequence; establishing an ideal output power model and a crystal structure change model based on the internal structure complete indexes and the environmental parameters, and obtaining ideal output power and a crystal structure change rate; drawing a power curve and analyzing and determining a state index of the solar battery pack; calculating a comprehensive evaluation index to evaluate a solar power generation operation state; the invention aims to realize comprehensive and accurate monitoring and evaluation of solar power generation operation by monitoring a crystal structure in a solar battery pack and establishing an evaluation model which comprehensively considers multiple factors.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation monitoring, and in particular to a method for monitoring the operation of solar power generation. Background Art

[0002] In the early days, solar power generation monitoring focused on simple power output measurements and basic environmental parameter collection, such as light intensity and temperature. These monitoring methods were relatively crude and could only provide limited information for evaluating the performance of solar cells. With the advancement of technology, monitoring systems have gradually been able to collect more parameters, including the battery's voltage, current and other electrical characteristics, and have begun to try to perform simple analysis on the collected data, such as calculating power generation efficiency. In recent years, with the rapid development of sensor technology, data analysis technology and computer technology, solar power generation monitoring technology has developed in a more intelligent and precise direction. Advanced sensors can measure various physical parameters more accurately. At the same time, data analysis algorithms have become more complex and efficient, and can conduct in-depth mining and analysis of a large amount of monitoring data to achieve a more comprehensive and accurate evaluation of solar power generation systems.

[0003] However, existing solar power generation monitoring technology mainly focuses on the monitoring of the external electrical characteristics of the battery and macro-environmental factors. Although these factors have an important impact on power generation performance, they ignore the impact of changes in the internal crystal structure of the battery on power generation efficiency. The integrity of the crystal structure inside the solar cell is directly related to the migration and recombination process of carriers, which in turn affects the photoelectric conversion efficiency of the battery. With the passage of time and the influence of environmental factors, the crystal structure will change, such as defects or lattice constant deviations. At the same time, the current evaluation methods are often based on simple indicators or models, which cannot fully consider the combined impact of multiple factors, which leads to the evaluation of the operating status of the solar power generation system is not comprehensive and accurate enough.

[0004] Therefore, there is an urgent need in the art for a solar power generation operation monitoring method to solve the above problems. Summary of the invention

[0005] The present invention provides a solar power generation operation monitoring method, which aims to achieve comprehensive and accurate monitoring and evaluation of solar power generation operation by monitoring the internal crystal structure of a solar cell group and establishing an evaluation model that comprehensively considers multiple factors.

[0006] The present invention provides a method for monitoring solar power generation operation, comprising:

[0007] Step 1: collecting the actual output power of the solar cell group in a preset period according to a time series, and outputting a number of actual output power values ​​in the period;

[0008] Step 2: At the beginning of each cycle, the crystal structure inside the solar cell group is monitored by high-resolution microscopy combined with spectral analysis technology to determine the crystal structure integrity index of the solar cell group in that cycle;

[0009] Step 3, collecting environmental parameters corresponding to the time series of actual output power values;

[0010] Step 4: Establish an ideal output power model and a crystal structure change model based on the internal structure integrity index and environmental parameters, and obtain several ideal output powers corresponding to the actual output power value, as well as the crystal structure change rate of the cycle;

[0011] Step 5: Draw a power curve based on the actual output power value and the ideal output power, and determine the state index of the solar cell group in the cycle through comparative analysis;

[0012] Step six, calculating a comprehensive evaluation index based on the state index and the crystal structure change rate, which is used to evaluate the operating state of solar power generation.

[0013] According to a solar power generation operation monitoring method provided by the present invention, in step 1, the actual output power value collection process includes:

[0014] Predetermine the period and sampling interval;

[0015] Connect a power meter to the output end of the solar cell array and measure the output power according to the sampling interval;

[0016] The measured output power is recorded in chronological order to form a time series of the cycle, that is, the cycle contains several actual output power values ​​P i(t) .

[0017] According to a solar power generation operation monitoring method provided by the present invention, in step 2, the process of determining the crystal structure integrity index of the solar cell group of the cycle is:

[0018] The crystal defect density ρ and lattice constant deviation △a of this period were determined by high-resolution microscopy combined with spectral analysis technology;

[0019] Set the ideal value of crystal defect density ρ0 and the ideal value of lattice constant deviation △a0; the values ​​are determined by the battery pack supplier;

[0020] By formula The crystal structure integrity index C of the solar cell group of this period is calculated; wherein ω1 and ω2 are weight factors, and ω1+ω2=1, and the values ​​are set based on the characteristics of the battery material.

[0021] According to a solar power generation operation monitoring method provided by the present invention, in step 3, the time series acquisition environmental parameters corresponding to the actual output power value include: light intensity G i 、Humidity i , wind speed W i And the battery internal temperature T i .

[0022] According to a solar power generation operation monitoring method provided by the present invention, in step 4, the ideal output power model is:

[0023]

[0024] Among them, P fi(t) is the ideal output power, P0 is the rated output power under standard conditions, T0 is the reference battery temperature under standard conditions, and G0 is the reference light intensity under standard conditions; β1, β2, β3, and β4 are power regulation constants, which are respectively used to reflect the influence of changes in crystal structure integrity on output power, the influence of temperature changes on the carrier migration ability in the crystal structure, the proportional relationship of output power relative to the reference light intensity G0 when light intensity changes, and the influence of humidity changes and wind speed changes on output power; the values ​​of the power regulation constants β1, β2, β3, and β4 are determined based on experimental data fitting.

[0025] According to a solar power generation operation monitoring method provided by the present invention, in step 4, the crystal structure change model is:

[0026]

[0027] in, is the crystal structure change rate, k is the Boltzmann constant; E a The activation energy E represents the energy required to overcome the energy barrier during the crystal structure change process. The thermal effect of the crystal structure change at different temperatures is measured by thermal analysis technology, thereby indirectly inferring the activation energy E. a ; β5 and β6 are structural change adjustment constants, which are used to reflect the basic rate at which the crystal structure integrity index changes with time under environmental parameter conditions, and the degree of influence of humidity change and wind speed change on the crystal structure change rate. Their values ​​are obtained in the same way as the power adjustment constant; n and m are the integrity index correlation index and light intensity correlation index, respectively, which are used to reflect the nonlinear influence of crystal structure integrity on its own change rate and the nonlinear influence of light intensity on the crystal structure change rate. Their values ​​are determined by the historical data fitting method.

[0028] According to a solar power generation operation monitoring method provided by the present invention, in step 5, the process of determining the state index of the solar cell group in the cycle by comparative analysis includes:

[0029] The actual output power P of this cycle i(t) And the ideal output power P fi(t) As the ordinate, the acquisition time is used as the abscissa, and two power curves P are drawn. (t) and P f(t) ;

[0030] Calculate the actual output power curve P (t) And the ideal output power curve P f(t) The root mean square error Where N is the number of acquisition points determined based on the sampling interval;

[0031] Based on the formula S = e -αRMSE The state index S of the solar cell group within the period is calculated, where α is a positive constant used to adjust the sensitivity of the state index to the root mean square error, and its value is determined by data fitting based on historical data.

[0032] According to a solar power generation operation monitoring method provided by the present invention, in step six, the process of calculating the comprehensive evaluation index based on the state index and the crystal structure change rate includes:

[0033] The state index S of the solar cell group and the crystal structure change rate of the current cycle Substitute into the formula In the above example, we can obtain the comprehensive evaluation index D of the current cycle;

[0034] The larger the value of the comprehensive evaluation index D is, the more stable the operation of solar power generation is in the current cycle; the smaller the value of the comprehensive evaluation index D is, the more fluctuating the operation of solar power generation is in the current cycle.

[0035] Compared with the prior art, the beneficial effects of this application are:

[0036] This application not only focuses on the external electrical characteristics and macro-environmental factors of the solar cell group, but also monitors the crystal structure inside the cell through high-resolution microscopy combined with spectral analysis technology, considering the direct impact of the crystal structure integrity on the carrier migration and recombination process; considering both the internal structure and external environmental factors at the same time, it can more accurately evaluate the performance of the solar power generation system;

[0037] The present application accurately evaluates the solar cell group by establishing an ideal output power model and a crystal structure change model; by drawing the actual output power curve and the ideal output power curve, not only the numerical difference of the power is considered, but also the shape and change trend of the power curve. Compared with the prior art which simply compares the difference between the actual power and the theoretical power, the operating state of the solar cell group can be more accurately evaluated;

[0038] This application can carry out targeted optimization measures for solar cell arrays based on comprehensive evaluation indicators; for example, when the evaluation indicator value is low, the installation angle of the battery pack can be adjusted according to the specific situation, maintenance can be carried out to improve the internal structure, etc., to provide support for management personnel.

[0039] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0040] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 It is a flow chart of a solar power generation operation monitoring method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0044] Embodiment 1:

[0045] The present invention provides a method for monitoring the operation of solar power generation. Figure 1 ,include:

[0046] Step 1: collecting the actual output power of the solar cell group in a preset period according to a time series, and outputting a number of actual output power values ​​in the period;

[0047] Step 2: At the beginning of each cycle, the crystal structure inside the solar cell group is monitored by high-resolution microscopy combined with spectral analysis technology to determine the crystal structure integrity index of the solar cell group in that cycle;

[0048] Step 3, collecting environmental parameters corresponding to the time series of actual output power values;

[0049] Step 4: Establish an ideal output power model and a crystal structure change model based on the internal structure integrity index and environmental parameters, and obtain several ideal output powers corresponding to the actual output power value, as well as the crystal structure change rate of the cycle;

[0050] Step 5: Draw a power curve based on the actual output power value and the ideal output power, and determine the state index of the solar cell group in the cycle through comparative analysis;

[0051] Step six, calculating a comprehensive evaluation index based on the state index and the crystal structure change rate, which is used to evaluate the operating state of solar power generation.

[0052] The principle of the above embodiment is: by continuously measuring the actual output power of the solar cell group at different time points, the actual data of the performance change of the solar cell group over time can be obtained; using high-resolution microscopy and spectral analysis technology to regularly check the state of the internal crystal structure of the solar cell helps to understand the aging or damage of the material, thereby indirectly reflecting the changing trend of the battery efficiency; at the same time, various external conditions that affect the photovoltaic conversion efficiency (such as temperature, light intensity, etc.) are collected to provide basic information for establishing a more accurate energy prediction model; combining the above two aspects of data to establish an ideal output power model and a crystal structure change model, and calculate the expected optimal working performance value based on this; then compare these theoretical values ​​with the measured results to identify potential problem areas; finally, based on the results of the comparative analysis, the health of the entire system is evaluated, and corresponding maintenance suggestions can be given.

[0053] The beneficial effects of the above embodiments are: timely discovery and resolution of potential fault hazards, reducing the risk of unexpected downtime; by continuously tracking the status of key components, appropriate maintenance measures can be taken to delay the aging process of equipment; based on accurate data support, operational strategies can be adjusted to maximize the use of renewable energy even under adverse conditions; long-term accumulated big data analysis helps to reveal new laws and promote scientific and technological progress and development in related fields.

[0054] In order to further optimize the above embodiment, in step 1, the process of collecting the actual output power value includes:

[0055] Predetermine the period and sampling interval;

[0056] Connect a power meter to the output end of the solar cell array and measure the output power according to the sampling interval;

[0057] The measured output power is recorded in chronological order to form a time series of the cycle, that is, the cycle contains several actual output power values ​​P i(t) .

[0058] It should be noted that the preset cycle is determined according to the application scenario and monitoring requirements of the solar power generation system. For example, if it is used for daily monitoring of a small distributed solar power generation system, one day may be selected as a cycle so as to timely understand the daily power generation situation. For large solar power stations, one week or one month may be selected as the cycle, because the performance of such systems changes relatively slowly, and a longer cycle can reduce the amount of data processing while also reflecting longer-term operating trends. The selection of the sampling interval should strike a balance between data accuracy and system resource consumption. If the sampling interval is too small, a large amount of data will be generated, increasing the burden of data processing and storage. If the sampling interval is too large, some important power change information may be missed. For some application scenarios that are more sensitive to fluctuations in power generation efficiency, such as high-precision solar research experiments, a shorter sampling interval may be selected, such as collecting data every 1-5 minutes. For general commercial solar power generation system monitoring, a sampling interval of 10-30 minutes can usually meet the needs.

[0059] Choose a high-precision, high-reliability power meter, whose measurement accuracy should meet the requirements of solar power generation system monitoring; for example, for small solar cell groups, a measurement accuracy of ±0.5%-±1% may be sufficient; for large solar power stations, a higher-precision meter may be required, such as a measurement accuracy of ±0.1%-±0.2%; correctly connect the power meter to the output end of the solar cell group to ensure that the connection is firm to avoid measurement errors caused by poor contact; at each sampling moment, the power meter measures the output power of the solar cell group in real time; during the measurement process, ensure that the measurement environment is stable to avoid the influence of external interference factors on the measurement results; for example, avoid electromagnetic interference and excessive temperature changes on the meter; at the same time, the meter should have an automatic calibration function to calibrate the measurement results regularly to ensure the accuracy of the measurement;

[0060] The output power value obtained from each measurement is stored in a database or data file; in order to facilitate subsequent analysis and processing, each power value should be accompanied by a corresponding timestamp to record the time of measurement; a standard data format, such as CSV (comma separated value) format, can be used to record the timestamp and power value in the file in sequence; for example, a row of data may be recorded as "2023-08-1510:00:00,150.2", where "2023-08-1510:00:00" is the timestamp and "150.2" is the measured output power value (unit: watt); by continuously recording the measured output power values, a time series of the actual output power values ​​within the period is formed over time.

[0061] In order to further optimize the above embodiment, in step 2, the process of determining the crystal structure integrity index of the periodic solar cell group is as follows:

[0062] The crystal defect density ρ and lattice constant deviation △a of this period were determined by high-resolution microscopy combined with spectral analysis technology;

[0063] Set the ideal value of crystal defect density ρ0 and the ideal value of lattice constant deviation △a0; the values ​​are determined by the battery pack supplier;

[0064] By formula The crystal structure integrity index C of the solar cell group of this period is calculated; wherein ω1 and ω2 are weight factors, and ω1+ω2=1, and the values ​​are set based on the characteristics of the battery material.

[0065] It should be noted that a high-resolution microscope is used to observe the crystal structure inside the solar cell group; the microscope should have a high enough resolution to clearly distinguish defects in the crystal, such as dislocations, vacancies, interstitial atoms, etc.; by observing and counting crystals in different areas multiple times, the number and distribution of crystal defects can be obtained; the images taken by the microscope are processed and analyzed with the help of professional image analysis software; these software can automatically identify crystal defects, classify and count them; by analyzing a large number of images, more accurate crystal defect density data can be obtained; for example, the number of defects per unit area is calculated to obtain the crystal defect density; the lattice constant of the crystal inside the solar cell group is measured using X-ray diffraction technology; the lattice constant of the crystal can be determined by measuring the diffraction angle and intensity of X-rays in the crystal; the measured lattice constant is compared with the standard value (provided by the battery pack supplier or determined based on the theoretical value of the crystal material) to calculate the lattice constant deviation;

[0066] The value of the weight factor should be determined based on existing research and experimental data or experiments; consult relevant academic literature and research reports to understand the research results of the same type of battery materials in terms of crystal structure; these studies may have analyzed and quantified the impact of factors such as crystal defect density and lattice constant deviation on performance; at the same time, combine your own experimental data to provide a reference for the setting of the weight factor; for example, battery samples with different crystal structure integrity can be prepared, and by controlling factors such as crystal defect density and lattice constant deviation, they can have different structural states; then, these samples are tested for their photoelectric performance, and their output power, photoelectric conversion efficiency and other indicators are measured; the weight coefficient is obtained in this way, or it can be directly requested from the battery pack supplier, which is a prior art and will not be elaborated on in detail.

[0067] In order to further optimize the above embodiment, in step 3, the time series of environmental parameters corresponding to the actual output power value includes: light intensity G i 、Humidity i , wind speed W iAnd the battery internal temperature T i .

[0068] It should be noted that for light intensity collection, a suitable light intensity sensor is selected. Common ones include silicon photocell sensors, photodiode sensors, etc. The light intensity sensor is installed near the solar cell group, and it is necessary to ensure that the sensor can receive similar lighting conditions as the battery group. It is usually installed above or on the side of the battery group to avoid being blocked. At the same time, the orientation of the sensor should be considered so that it can receive sunlight to the greatest extent. For example, if the solar cell group is installed facing south, the light intensity sensor should also be installed facing south; the sensor collects light intensity data in real time and records it in correspondence with the time series of the actual output power value. The data collected by the sensor can be stored in a database or data file at regular intervals using a data acquisition system. For example, at a certain sampling interval (such as the same as the power value collection interval), the light intensity value at the current moment and the corresponding power value are recorded together; the humidity, wind speed, and internal battery temperature are the same, and no further elaboration is required.

[0069] In order to further optimize the above embodiment, in step 4, the ideal output power model is:

[0070]

[0071] Among them, P fi(t) is the ideal output power, P0 is the rated output power under standard conditions, T0 is the reference battery temperature under standard conditions, and G0 is the reference light intensity under standard conditions; β1, β2, β3, and β4 are power regulation constants, which are respectively used to reflect the influence of changes in crystal structure integrity on output power, the influence of temperature changes on the carrier migration ability in the crystal structure, the proportional relationship between the output power and the reference light intensity G0 when the light intensity changes, and the influence of humidity changes and wind speed changes on the output power; the values ​​of the power regulation constants β1, β2, β3, and β4 are determined based on fitting of experimental data.

[0072] It should be noted that the ideal output power model comprehensively considers the impact of multiple factors on the output power of the solar cell group. First, consider the impact of the integrity of the crystal structure on the output power. As the integrity of the crystal structure changes, the migration of carriers inside the crystal will change, thus affecting the output power. Secondly, temperature affects the carrier migration ability in the crystal structure. Changes in temperature will cause changes in the carrier migration ability, which in turn affects the output power. Light intensity is also a key factor. When the light intensity changes, the output power will change relative to the reference light intensity, and this change is not a simple linear relationship. Finally, humidity and wind speed will also affect the output power. Changes in humidity and wind speed may affect the heat dissipation, surface state, etc. of the battery pack, thereby affecting the output power.

[0073] The method for determining the power regulation constant based on experimental data fitting includes: designing a series of experiments to measure the output power of a solar cell group under different conditions of crystal structure integrity, temperature, light intensity, humidity and wind speed; for example, the crystal structure integrity can be changed by controlling the crystal growth conditions, the temperature can be changed by a heating or cooling device, the light intensity can be changed by a shading or supplementary lighting device, the humidity can be changed by a humidifying or dehumidifying device, and the wind speed can be changed by a fan or a wind shield; under each experimental condition, the output power of the solar cell group is accurately measured, and the corresponding crystal structure integrity index, temperature, light intensity, humidity and wind speed data are recorded; using a data fitting algorithm, such as the least squares method, the experimental data is substituted into an ideal output power model (the variables in the model are replaced with actual measured values); then by adjusting the value of the power regulation constant, the output power calculated by the model is made to match the actual measured output power as closely as possible; and this process is repeated until a set of power regulation constants is found so that the model can better fit the actual data under all experimental conditions.

[0074] In order to further optimize the above embodiment, in step 4, the crystal structure change model is:

[0075]

[0076] in, is the crystal structure change rate, k is the Boltzmann constant; E a The activation energy E represents the energy required to overcome the energy barrier during the crystal structure change process. The thermal effect of the crystal structure change at different temperatures is measured by thermal analysis technology, thereby indirectly inferring the activation energy E. a ; β5 and β6 are structural change adjustment constants, which are used to reflect the basic rate at which the crystal structure integrity index changes with time under environmental parameter conditions, and the degree of influence of humidity change and wind speed change on the crystal structure change rate. Their values ​​are obtained in the same way as the power adjustment constant; n and m are the integrity index correlation index and light intensity correlation index, respectively, which are used to reflect the nonlinear influence of crystal structure integrity on its own change rate and the nonlinear influence of light intensity on the crystal structure change rate. Their values ​​are determined by the historical data fitting method.

[0077] It should be noted that this model is used to describe the changes in the crystal structure inside the solar cell group over time; first, the rate of change of the crystal structure is affected by the activation energy; the activation energy is the energy barrier that needs to be overcome in the process of crystal structure change. The higher the temperature, the higher the energy of the atoms, and the easier it is to overcome the activation energy, thereby changing the crystal structure; secondly, the crystal structure integrity index itself has a nonlinear effect on its change rate; when the integrity of the crystal structure decreases, it may accelerate its further deterioration, and this relationship is reflected by the complete index related index; light intensity also has a nonlinear effect on the rate of change of the crystal structure; as the light intensity changes, it may affect the electronic state and chemical bonds inside the crystal, and then affect the rate of change of the crystal structure, which is reflected by the light intensity related index; finally, humidity and wind speed in the environmental parameters will also affect the rate of change of the crystal structure; changes in humidity and wind speed may change the physical and chemical environment on the surface of the crystal, thereby affecting the rate of change of the crystal structure;

[0078] The activation energy can be measured by thermal analysis techniques, such as differential scanning calorimetry (DSC), to measure the thermal effect of crystal structure changes at different temperatures. When the crystal structure changes, it absorbs or releases heat. By measuring these heat changes and the corresponding temperature changes, the value of the activation energy can be indirectly inferred.

[0079] The structural change adjustment constant can be obtained in the same way as the power adjustment constant; that is, a series of experiments are designed to observe the changes of the crystal structure integrity index over time under different environmental parameter conditions (including different humidity, wind speed, temperature, light intensity and crystal structure integrity), and the corresponding data are recorded; then a data fitting algorithm, such as the least squares method, is used to substitute the experimental data into the crystal structure change model, and by adjusting the value of the structural change adjustment constant, the crystal structure change rate calculated by the model is made to match the actual observed change rate as closely as possible;

[0080] The complete indicator correlation index and the light intensity correlation coefficient can be determined by the historical data fitting method; collect the crystal structure change rate data observed in the past under different crystal structure integrity and light intensity conditions; then substitute these data into the crystal structure change model, and adjust the values ​​of the complete indicator correlation index and the light intensity correlation coefficient so that the model can better fit the historical data, thereby determining the values ​​of these two indexes.

[0081] In order to further optimize the above embodiment, in step 5, the process of determining the state index of the solar cell group in the cycle through comparative analysis includes:

[0082] The actual output power P of this cycle i(t) And the ideal output power P fi(t)As the ordinate, the acquisition time is used as the abscissa, and two power curves P are drawn. (t) and P f(t) ;

[0083] Calculate the actual output power curve P (t) And the ideal output power curve P f(t) The root mean square error Where N is the number of acquisition points determined based on the sampling interval;

[0084] Based on the formula S = e -αRMSE The state index S of the solar cell group within the period is calculated, where α is a positive constant used to adjust the sensitivity of the state index to the root mean square error, and its value is determined by data fitting based on historical data.

[0085] It should be noted that the purpose of drawing two power curves is to intuitively compare the changes in the actual output power and the ideal output power in the time series; taking the acquisition time as the horizontal axis, the difference between the actual power and the ideal power at different times can be clearly seen; taking the actual output power and the ideal output power of this cycle as the vertical axis, two curves can be drawn in the same coordinate system, one representing the actual situation and the other representing the ideal situation;

[0086] RMSE is a statistical indicator that measures the degree of difference between two curves. It is obtained by calculating the square root of the average of the sum of the squares of the difference between the actual power and the ideal power at each sampling point. The smaller the RMSE value, the closer the two curves are, that is, the smaller the difference between the actual output power and the ideal output power is.

[0087] The value of α is determined by data fitting based on historical data; the specific method is: collect actual power data and ideal power data of multiple cycles in the past, and calculate the RMSE value of each cycle; at the same time, conduct a subjective evaluation of the operating status of the solar cell group in each cycle according to the actual situation, and divide it into different levels, such as "normal", "slightly abnormal", "moderately abnormal" and "severely abnormal", and assign corresponding experience values ​​of the status indicators respectively; then substitute the calculated RMSE and the subjective evaluation value into the formula, and use the data fitting method (such as the least squares method) to adjust the value of α, so that the value calculated by the formula is as consistent as possible with the subjective evaluation value; through multiple experiments and data fitting, the optimal value of α is finally determined;

[0088] When RMSE increases, the state index S will decrease; this more sensitively reflects the deterioration of the operating state; the value range of the state index is from 0 (severe abnormality) to 1 (normal operation). The value of S can intuitively understand how close the operating state of the solar cell group is to the ideal state during the cycle.

[0089] In order to further optimize the above embodiment, in step six, the process of calculating the comprehensive evaluation index based on the state index and the crystal structure change rate includes:

[0090] The state index S of the solar cell group and the crystal structure change rate of the current cycle Substitute into the formula In the above example, we can obtain the comprehensive evaluation index D of the current cycle;

[0091] The larger the value of the comprehensive evaluation index D is, the more stable the operation of solar power generation is in the current cycle; the smaller the value of the comprehensive evaluation index D is, the more fluctuating the operation of solar power generation is in the current cycle.

[0092] It should be noted that the comprehensive evaluation index is calculated by substituting the state index and the crystal structure change rate into a specific formula, which aims to comprehensively consider the internal structure changes of the solar cell group (reflected by the crystal structure change rate) and the degree of deviation between the actual operating state and the ideal state (reflected by the state index), so as to comprehensively evaluate the operating state of solar power generation; when the value of the comprehensive evaluation index is larger, it means that the solar cell group operates more stably in the current cycle; this is because a larger index value means that the crystal structure change rate may be in a more favorable range (such as the crystal structure integrity decreases slowly or even improves), and the state index also shows that the actual power output is closer to the ideal power output, both of which are conducive to the stable operation of solar power generation;

[0093] On the contrary, when the value of the comprehensive evaluation index is smaller, it means that the operation of solar power generation is more volatile in the current cycle; the smaller index value may be due to poor crystal structure change rate (such as rapid decline in crystal structure integrity), or the status indicator shows that the actual power is significantly different from the ideal power, or both. These situations will lead to unstable operation of solar power generation and power fluctuations.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring solar power generation operation, characterized in that: include: Step 1: collecting the actual output power of the solar cell group in a preset period according to a time series, and outputting a number of actual output power values ​​in the period; Step 2: At the beginning of each cycle, the crystal structure inside the solar cell group is monitored by high-resolution microscopy combined with spectral analysis technology to determine the crystal structure integrity index of the solar cell group in that cycle; Step 3, collecting environmental parameters corresponding to the time series of actual output power values; Step 4: Establish an ideal output power model and a crystal structure change model based on the internal structure integrity index and environmental parameters, and obtain several ideal output powers corresponding to the actual output power value, as well as the crystal structure change rate of the cycle; Step 5: Draw a power curve based on the actual output power value and the ideal output power, and determine the state index of the solar cell group in the cycle through comparative analysis; Step six, calculating a comprehensive evaluation index based on the state index and the crystal structure change rate, which is used to evaluate the operating state of solar power generation.

2. A solar power generation operation monitoring method according to claim 1, characterized in that: In step 1, the actual output power value acquisition process includes: Predetermine the period and sampling interval; Connect a power meter to the output end of the solar cell array and measure the output power according to the sampling interval; The measured output power is recorded in chronological order to form a time series of the cycle, that is, the cycle contains several actual output power values ​​P i(t) .

3. A solar power generation operation monitoring method according to claim 2, characterized in that: In step 2, the process of determining the crystal structure integrity index of the solar cell group of the period is: The crystal defect density ρ and lattice constant deviation Δa of the period were determined by high-resolution microscopy combined with spectral analysis technology; Set an ideal value of crystal defect density ρ0 and an ideal value of lattice constant deviation Δa0; the values ​​are determined by the battery pack supplier; By formula The crystal structure integrity index C of the solar cell group of this period is calculated; wherein ω1 and ω2 are weight factors, and ω1+ω2=1, and the values ​​are set based on the characteristics of the battery material.

4. A solar power generation operation monitoring method according to claim 3, characterized in that: In step 3, the time series of environmental parameters corresponding to the actual output power value includes: light intensity G i 、Humidity i , wind speed W i And the battery internal temperature T i .

5. A solar power generation operation monitoring method according to claim 4, characterized in that: In step 4, the ideal output power model is: Among them, P fi(t) is the ideal output power, P0 is the rated output power under standard conditions, T0 is the reference battery temperature under standard conditions, and G0 is the reference light intensity under standard conditions; β1, β2, β3, and β4 are power regulation constants, which are used to reflect the influence of changes in crystal structure integrity on output power, the influence of temperature changes on the carrier migration ability in the crystal structure, and the output power relative to the reference light intensity G when the light intensity changes. n The influence of the change proportional relationship, humidity change and wind speed change on the output power; the values ​​of the power regulation constants β1, β2, β3, and β4 are determined based on experimental data fitting.

6. A method for monitoring solar power generation operation according to claim 5, characterized in that: In step 4, the crystal structure change model is: in, is the crystal structure change rate, k is the Boltzmann constant; E a The activation energy E represents the energy required to overcome the energy barrier during the crystal structure change process. The thermal effect of the crystal structure change at different temperatures is measured by thermal analysis technology, thereby indirectly inferring the activation energy E. a ; β5 and β6 are structural change adjustment constants, which are used to reflect the basic rate at which the crystal structure integrity index changes with time under environmental parameter conditions, and the degree of influence of humidity change and wind speed change on the crystal structure change rate. Their values ​​are obtained in the same way as the power adjustment constant; n and m are the integrity index correlation index and light intensity correlation index, respectively, which are used to reflect the nonlinear influence of crystal structure integrity on its own change rate and the nonlinear influence of light intensity on the crystal structure change rate. Their values ​​are determined by the historical data fitting method.

7. A solar power generation operation monitoring method according to claim 6, characterized in that: In step 5, the process of determining the state index of the solar cell group in the cycle through comparative analysis includes: The actual output power P of this cycle i(t) And the ideal output power P fi(t) As the ordinate, the acquisition time is used as the abscissa, and two power curves P are drawn. (t) and P f(t) ; Calculate the actual output power curve P (t) And the ideal output power curve P f(t) The root mean square error Where N is the number of acquisition points determined based on the sampling interval; Based on the formula S = e -αRMSE The state index S of the solar cell group within the period is calculated, where α is a positive constant used to adjust the sensitivity of the state index to the root mean square error, and its value is determined by data fitting based on historical data.

8. A method for monitoring solar power generation operation according to claim 7, characterized in that: In step six, the process of calculating the comprehensive evaluation index based on the state index and the crystal structure change rate includes: The state index S of the solar cell group and the crystal structure change rate of the current cycle Substitute into the formula In the above example, we can obtain the comprehensive evaluation index D of the current cycle; The larger the value of the comprehensive evaluation index D is, the more stable the operation of solar power generation is in the current cycle; the smaller the value of the comprehensive evaluation index D is, the more fluctuating the operation of solar power generation is in the current cycle.

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