A reliability evaluation method for photovoltaic arrays

Abstract

The present invention provides a reliability evaluation method for a photovoltaic array, which includes the following steps: obtaining historical data; taking the ratio of the actual power generation of the photovoltaic array to the theoretical power generation within a period of time as a preliminary indicator of the performance of the photovoltaic array; correcting the preliminary indicator to obtain a corrected final indicator data set; obtaining the probability density function value corresponding to each photovoltaic array; and taking the ratio of the maximum probability density function value of the target photovoltaic array to the maximum probability density function value of all photovoltaic arrays as the reliability evaluation value of the target photovoltaic array. The method can intuitively reflect the reliability of the photovoltaic array, and the evaluation index is easy to understand, which is of great significance to improving the operation and maintenance efficiency of photovoltaic power stations and evaluating the performance of photovoltaic arrays.

Description

Technical Field

[0001] The invention belongs to the technical field of photovoltaic array performance evaluation, and specifically relates to a reliability evaluation method for a photovoltaic array. Background Art

[0002] In recent years, the photovoltaic industry has developed rapidly. However, as an important part of photovoltaic power stations, photovoltaic arrays are prone to various failures when exposed to outdoor and harsh environments for a long time. At the same time, due to the series-parallel structure of photovoltaic arrays, a failure of one module will reduce the efficiency of the entire array, affect the performance of the power station, and even threaten the safety of the photovoltaic power station. Therefore, the reliability of the array is the key to ensuring the operation of the entire power station, and it is of great significance to establish a performance evaluation model for photovoltaic arrays.

[0003] At present, there are few parameters available for fault diagnosis and performance evaluation of photovoltaic arrays, and most of them are analyzed from the current, voltage, and power of the array. PR, as an important indicator for evaluating the quality of photovoltaic power stations, can comprehensively reflect the operating status of the power station. However, in actual projects, since the calculation of PR value is related to variables such as irradiance and output power, the output of photovoltaic arrays usually fluctuates greatly and irregularly, it is very easy to cause misjudgment by directly using PR for fault diagnosis and performance evaluation. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, in order to enable PR with uncertainty to evaluate photovoltaic arrays, the present invention provides a reliability evaluation method for photovoltaic arrays. By performing statistical analysis on the corrected array PR, the concept of array reliability is introduced on this basis. This method can assist users in effectively evaluating the performance of photovoltaic arrays using the array PR indicator.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0006] A method for evaluating the reliability of a photovoltaic array is provided, comprising the following steps:

[0007] S1, acquiring and preprocessing historical data of different photovoltaic arrays in the same area to obtain preprocessed historical data of photovoltaic arrays;

[0008] S2. One thousandth of the product of irradiance and the nominal capacity of the photovoltaic array is taken as the theoretical power generation, and the ratio of the actual power generation of the photovoltaic array over a period of time to the theoretical power generation is taken as the preliminary indicator of the performance of the photovoltaic array;

[0009] S3, obtaining a temperature correction coefficient based on the preprocessed historical data of the photovoltaic array;

[0010] S4, using the temperature correction coefficient to correct the preliminary index of the photovoltaic array performance to obtain a corrected photovoltaic array performance index, i.e., a final index;

[0011] S5. Set the morning and evening time periods, obtain the sampling points with the largest difference between two adjacent final indicators in the morning and evening time periods of the same day as inflection points, and obtain the average irradiance corresponding to the two inflection points;

[0012] S6. Delete the final index of the data points whose irradiance in the morning and evening time periods is less than the corresponding irradiance mean value, and obtain a corrected final index data set corresponding to each photovoltaic array in each day;

[0013] S7. Based on the corrected final indicator data set, obtain the probability density function value corresponding to each photovoltaic array; and take the ratio of the maximum probability density function value of the target photovoltaic array to the maximum probability density function value of all photovoltaic arrays as the reliability evaluation value of the target photovoltaic array.

[0014] Furthermore, the historical data of photovoltaic arrays preprocessed in step S1 include the number of photovoltaic arrays in the same area, the actual power generation of each photovoltaic array at each sampling point on the same day and the irradiance obtained by the power station in the area, the ambient temperature of the photovoltaic cells under the nominal operating temperature conditions, the nominal operating temperature of the photovoltaic cells, the irradiance of the photovoltaic cells under the nominal operating temperature conditions, and the ambient temperature.

[0015] Furthermore, the specific method of step S3 is:

[0016] According to the formula:

[0017]

[0018] Get the temperature correction factor K c ; where T a is the ambient temperature; G T G is the irradiance received by the photovoltaic cell per unit area; N is the irradiance of the photovoltaic cell under nominal operating temperature conditions; T N is the nominal operating temperature of the photovoltaic cell; T a,N is the ambient temperature of the photovoltaic cell under the nominal operating temperature conditions; T STC is the temperature under standard test conditions; δ is the power temperature coefficient of the photovoltaic cell.

[0019] Furthermore, the specific method of step S4 is:

[0020] According to the formula:

[0021]

[0022] Get the corrected photovoltaic array performance index PR, that is, the final index PR; where PR * It is a preliminary indicator of photovoltaic array performance; K c is the temperature correction factor.

[0023] Furthermore, the specific method of step S5 includes the following sub-steps:

[0024] S5-1, the first q1 sampling points of all photovoltaic arrays in a day are regarded as the early time period, and the last q2 sampling points of a day are regarded as the late time period;

[0025] S5-2, obtaining the sampling points with the largest difference between two adjacent final indicators in the morning time period and the evening time period of the same day as the inflection points, that is, obtaining the inflection points of the early time period and the late time period of each photovoltaic array in each day;

[0026] S5-3. For the turning point of the a-th photovoltaic array in the early period of the b-th day Get the average irradiance of the photovoltaic array at the sampling point on all days, that is, the early turning point of the a-th photovoltaic array on the b-th day The corresponding average irradiance

[0027] For the a-th photovoltaic array at the late time of day b, the inflection point Get the average irradiance of the photovoltaic array at the sampling point on all days, that is, the inflection point of the a-th photovoltaic array in the late time period of the b-th day The corresponding average irradiance

[0028] Furthermore, the early time period is the first 90 minutes, and the late time period is the last 60 minutes; when the sampling interval is 10 minutes, the value of q1 is 9, and the value of q2 is 6.

[0029] Furthermore, the specific method of step S6 is:

[0030] Get the average value of the irradiance of the a-th photovoltaic array in the early time period of the b-th day when it is less than the irradiance The final index of the sampling point is deleted; the irradiance of the a-th photovoltaic array in the evening time period of the b-th day is less than the average value of the irradiance The final index of the sampling point is deleted; and the corrected final index data set corresponding to each photovoltaic array on each day is obtained.

[0031] Furthermore, the specific method for obtaining the probability density function value corresponding to the photovoltaic array in step S7 is:

[0032] According to the formula:

[0033]

[0034]

[0035] M a =d·m

[0036] Get the probability density function value corresponding to the a-th photovoltaic array when the set performance index is x Where π is a constant; exp represents an exponential function with the natural constant e as the base; h is the bandwidth; M a represents the total number of final indicators of the a-th photovoltaic array in a total of d days; m is the total number of final indicators corrected in one day; σ is the M corresponding to the a-th photovoltaic array a The standard deviation of the final corrected indicator; represents the final index of the ith corrected value in the ath photovoltaic array; when x changes, the probability density function value corresponding to the photovoltaic array Follow the changes.

[0037] The beneficial effects of the present invention are:

[0038] The present invention provides a performance calculation method and reliability evaluation method for a photovoltaic array. By statistically analyzing the modified array PR, the concept of array reliability is introduced on this basis. This method can assist users in effectively evaluating the performance of a photovoltaic array using the array PR index. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flowchart of the method is shown in FIG.

[0040] Figure 2 This is the array PR effect diagram before correction based on irradiance analysis;

[0041] Figure 3 This is the PR effect diagram of the array after correction based on irradiance analysis;

[0042] Figure 4 is the probability density curve corresponding to 553 photovoltaic arrays of the photovoltaic power station in the embodiment;

[0043] Figure 5 The reliability of 553 photovoltaic arrays in the photovoltaic power station. DETAILED DESCRIPTION

[0044] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0045] Example

[0046] The data in this embodiment comes from a photovoltaic power station in a plain in China. There are 553 arrays in the same area of ​​the photovoltaic power station. The photovoltaic system collects data every ten minutes, mainly including array current, voltage, power data and irradiance, ambient temperature, humidity and other meteorological data. Figure 1 The figure shows the performance calculation method and reliability evaluation method flow chart of photovoltaic array. The specific steps of the method flow are as follows:

[0047] S1, acquiring and preprocessing historical data of different photovoltaic arrays in the same area to obtain preprocessed historical data of photovoltaic arrays;

[0048] S2. Take one thousandth of the product of irradiance and the nominal capacity of the photovoltaic array as the theoretical power generation, and take the ratio of the actual power generation of the photovoltaic array over a period of time to the theoretical power generation as the preliminary indicator of the performance of the photovoltaic array PR. * ;

[0049] S3, obtaining a temperature correction coefficient based on the preprocessed historical data of the photovoltaic array;

[0050] S4, using the temperature correction coefficient to correct the preliminary index of the photovoltaic array performance to obtain a corrected photovoltaic array performance index, i.e., a final index;

[0051] S5. Set the morning and evening time periods, obtain the sampling points with the largest difference between two adjacent final indicators in the morning and evening time periods of the same day as inflection points, and obtain the average irradiance corresponding to the two inflection points;

[0052] S6. Delete the final index of the data points whose irradiance in the morning and evening time periods is less than the corresponding irradiance mean value, and obtain a corrected final index data set corresponding to each photovoltaic array in each day;

[0053] S7. Based on the corrected final indicator data set, obtain the probability density function value corresponding to each photovoltaic array; and take the ratio of the maximum probability density function value of the target photovoltaic array to the maximum probability density function value of all photovoltaic arrays as the reliability evaluation value of the target photovoltaic array.

[0054] In the specific implementation process, the specific method for preprocessing historical meteorological data is: deleting unreasonable data and low irradiance data.

[0055] In practice, since the irradiance is obtained by other equipment (not the photovoltaic array), the irradiance of the photovoltaic array may be different from the measured irradiance due to the array installation inclination, placement, solar azimuth, etc., resulting in PR * The problem is that it cannot reflect the real situation. * Perform corrections and data filtering. Figure 2 and Figure 3 The following are the array PR effect diagrams before and after the correction based on irradiance analysis. It can be seen from the figure that the corrected PR value is more in line with the actual situation.

[0056] In many practical situations, the distribution characteristics of sample data are not like some common probability distributions, that is, it is difficult to fit them with a certain distribution, especially when the data presents a bimodal or multimodal distribution, the matching degree between the parametric density estimation and the actual sample distribution is low. Unlike parametric density estimation, non-parametric estimation does not rely on prior knowledge, but focuses on the characteristics of the data itself to fit the distribution. It has a good fitting effect for samples with bimodal and multimodal distributions. For the case of a large number of sample points, waveform synthesis will occur between adjacent peaks of the probability density curve. Considering the ease of calculation of waveform synthesis, the probability density function selected is expressed as:

[0057]

[0058] Where π is a constant; exp represents an exponential function with the natural constant e as the base; h is the bandwidth; M a represents the total number of final indicators of the a-th photovoltaic array in a total of d days; m is the total number of final indicators corrected in one day; σ is the M corresponding to the a-th photovoltaic array a The standard deviation of the final corrected indicator; represents the final index of the ith corrected value in the ath photovoltaic array; when x changes, the probability density function value corresponding to the photovoltaic array The probability density curve of the 553 photovoltaic arrays in the whole station is as follows: Figure 4 shown.

[0059] The peak of the probability density curve indicates that the corresponding PR value has the highest probability of occurrence. A large peak value indicates that many real-time PRs of the array are near the PR corresponding to the peak value, that is, relatively few PRs are in other locations. The ratio of the maximum probability density function value of the target photovoltaic array to the maximum probability density function value of all photovoltaic arrays is used as the reliability evaluation value of the target photovoltaic array. The average value of the photovoltaic array reliability can be used to score the reliability of each array of the entire station (the full score is 1 point), 0.7-1 points for excellent reliability, 0.4-0.7 points for good reliability, 0.3-0.4 points for medium reliability, and 0-0.3 points for poor reliability, which can reflect the reliability ranking percentage of the entire station array. The array reliability of the 553 arrays in the entire station is as follows: Figure 5 shown.

[0060] In summary, the present invention provides a reliability evaluation method for a photovoltaic array. By performing statistical analysis on the corrected final indicators of the photovoltaic array, the concept of array reliability is introduced on this basis. This method can assist users in using the array PR indicators (corrected final indicator data set) to effectively evaluate the performance and reliability of the photovoltaic array, which is of great significance for improving the operation and maintenance efficiency of photovoltaic power stations and evaluating the performance of photovoltaic arrays.

[0061] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims be included in the present invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0062] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A reliability evaluation method for a photovoltaic array, characterized in that: The following steps are involved: S1, acquiring and preprocessing historical data of different photovoltaic arrays in the same area to obtain preprocessed historical data of photovoltaic arrays; S2. One thousandth of the product of irradiance and the nominal capacity of the photovoltaic array is taken as the theoretical power generation, and the ratio of the actual power generation of the photovoltaic array over a period of time to the theoretical power generation is taken as the preliminary indicator of the performance of the photovoltaic array; S3, obtaining a temperature correction coefficient based on the preprocessed historical data of the photovoltaic array; S4, using the temperature correction coefficient to correct the preliminary index of the photovoltaic array performance to obtain a corrected photovoltaic array performance index, i.e., a final index; S5. Set the morning and evening time periods, obtain the sampling points with the largest difference between two adjacent final indicators in the morning and evening time periods of the same day as inflection points, and obtain the average irradiance corresponding to the two inflection points; S6. Delete the final index of the data points whose irradiance in the morning and evening time periods is less than the corresponding irradiance mean value, and obtain a corrected final index data set corresponding to each photovoltaic array in each day; S7. Based on the corrected final indicator data set, obtain the probability density function value corresponding to each photovoltaic array; take the ratio of the maximum probability density function value of the target photovoltaic array to the maximum probability density function value of all photovoltaic arrays as the reliability evaluation value of the target photovoltaic array; The specific method of step S3 is: According to the formula: Get the temperature correction factor K c ; where Τ a is the ambient temperature; G T G is the irradiance received by the photovoltaic cell per unit area; N is the irradiance of the photovoltaic cell under nominal operating temperature conditions; T N is the nominal operating temperature of the photovoltaic cell; T a,N is the ambient temperature of the photovoltaic cell under the nominal operating temperature conditions; STC is the temperature under standard test conditions; δ is the power temperature coefficient of the photovoltaic cell; The specific method of step S4 is: According to the formula: Get the corrected photovoltaic array performance index PR, that is, the final index PR; where PR * It is a preliminary indicator of photovoltaic array performance; K c is the temperature correction factor; The specific method for obtaining the probability density function value corresponding to the photovoltaic array in step S7 is: According to the formula: M a =d·m Get the probability density function value corresponding to the a-th photovoltaic array when the set performance index is x Where π is a constant; exp represents an exponential function with the natural constant e as the base; h is the bandwidth; M a represents the total number of final indicators of the a-th photovoltaic array in a total of d days; m is the total number of final indicators corrected in one day; σ is the M corresponding to the a-th photovoltaic array a The standard deviation of the final corrected indicator; represents the final index of the ith corrected value in the ath photovoltaic array; when x changes, the probability density function value corresponding to the photovoltaic array Follow the changes.

2. The reliability evaluation method of a photovoltaic array according to claim 1, characterized in that: The historical data of photovoltaic arrays preprocessed in step S1 include the number of photovoltaic arrays in the same area, the actual power generation of each photovoltaic array at each sampling point on the same day and the irradiance obtained by the power station in the area, the ambient temperature of the photovoltaic cells under the nominal operating temperature conditions, the nominal operating temperature of the photovoltaic cells, the irradiance of the photovoltaic cells under the nominal operating temperature conditions, and the ambient temperature.

3. The reliability evaluation method of a photovoltaic array according to claim 1, characterized in that: The specific method of step S5 includes the following sub-steps: S5-1, the first q1 sampling points of all photovoltaic arrays in a day are regarded as the early time period, and the last q2 sampling points of a day are regarded as the late time period; S5-2, obtaining the sampling points with the largest difference between two adjacent final indicators in the morning time period and the evening time period of the same day as the inflection points, that is, obtaining the inflection points of the early time period and the late time period of each photovoltaic array in each day; S5-3. For the turning point of the a-th photovoltaic array in the early period of the b-th day Get the average irradiance of the photovoltaic array at the sampling point on all days, that is, the early turning point of the a-th photovoltaic array on the b-th day The corresponding average irradiance For the a-th photovoltaic array at the late time of day b, the inflection point Get the average irradiance of the photovoltaic array at the sampling point on all days, that is, the inflection point of the a-th photovoltaic array in the late time period of the b-th day The corresponding average irradiance 4. The reliability evaluation method of a photovoltaic array according to claim 3, characterized in that: The early time period is the first 90 minutes, and the late time period is the last 60 minutes. When the sampling interval is 10 minutes, the value of q1 is 9 and the value of q2 is 6.

5. The reliability evaluation method of a photovoltaic array according to claim 3, characterized in that: The specific method of step S6 is: Get the average value of the irradiance of the a-th photovoltaic array in the early time period of the b-th day when it is less than the irradiance The final index of the sampling point is deleted; the irradiance of the a-th photovoltaic array in the evening time period of the b-th day is less than the average value of the irradiance The final index of the sampling point is deleted; The corrected final indicator data set corresponding to each photovoltaic array on each day is obtained.

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