A fault diagnosis method for photovoltaic combiner box

Abstract

The present invention relates to the technical field of photovoltaic equipment diagnosis, and specifically to a fault diagnosis method for photovoltaic combiner boxes. The method obtains the current data of electrical components and the voltage data of sampling circuits in electrical components at each moment within the time neighborhood of the current moment; obtains the current barrier coefficient of each electrical component at the current moment according to the current data distribution of the electrical components at the current moment; obtains the current fluctuation coefficient of each electrical component at the current moment according to the change trend of the current data of each electrical component within the time neighborhood of the current moment; obtains the failure probability of each sampling circuit in combination with the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood; and performs abnormal monitoring on electrical components. The present invention improves the accuracy of abnormal fault monitoring by analyzing the possibility of abnormal faults in each electrical component.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic equipment diagnosis, and in particular to a fault diagnosis method for a photovoltaic combiner box. Background Art

[0002] Photovoltaic combiner boxes can protect the stability of photovoltaic power generation systems. Due to the huge number of photovoltaic combiner boxes used, it is found in actual use that the electrical components inside the photovoltaic combiner boxes are prone to aging, short circuit, open circuit or other potential failures due to the use environment and use cycle during operation. Abnormal failures of electrical components in photovoltaic combiner boxes will greatly affect the stability of photovoltaic power generation systems. Therefore, identifying abnormal failures of electrical components in photovoltaic combiner boxes has important practical significance.

[0003] In the prior art, after the working power of an electrical component is determined through the performance of its various electrical parameters, a working power threshold monitoring method can be used for analysis. When the working power exceeds or falls below the set threshold, the system will trigger an abnormal alarm. However, due to the relatively small impact of early device aging and minor component damage on the working power of electrical components, the working power change at this time may not reach the threshold set based on relevant experience, and the abnormal fault of the electrical component is ignored, resulting in poor abnormal fault monitoring effect. Summary of the invention

[0004] In order to solve the technical problem that the working power threshold monitoring method cannot adapt to different operating time periods, resulting in poor monitoring effect of abnormal faults of electrical components, the purpose of the present invention is to provide a fault diagnosis method for a photovoltaic combiner box, and the technical solution adopted is as follows:

[0005] The present invention proposes a fault diagnosis method for a photovoltaic combiner box, the method comprising:

[0006] Obtaining the current data of the electrical component and the voltage data of the sampling circuit in the electrical component at each moment within the time neighborhood of the current moment;

[0007] According to the current data distribution of the electrical components at the current moment, the current barrier coefficient of each electrical component at the current moment is obtained; according to the change trend of the current data of each electrical component within the time neighborhood at the current moment, the current fluctuation coefficient of each electrical component at the current moment is obtained;

[0008] Obtaining the failure probability of each sampling circuit at the current moment according to the current barrier coefficient of each electrical component at the current moment, the current fluctuation coefficient, and the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood;

[0009] The electrical components are monitored according to the failure probability of each sampling circuit at the current moment.

[0010] Furthermore, the method for obtaining the current barrier coefficient includes:

[0011] At the current moment, the average value of the current data of all electrical components is calculated as the current average value;

[0012] The current barrier coefficient of each electrical component at the current moment is obtained based on the difference between the current mean and the current data of each electrical component, as well as the degree of fluctuation of the current data of all electrical components. The difference is positively correlated with the current barrier coefficient, and the degree of fluctuation is negatively correlated with the current barrier coefficient.

[0013] Furthermore, the method for obtaining the current fluctuation coefficient includes:

[0014] Constructing a current data sequence of each electrical component within a time neighborhood at the current moment, and obtaining a multi-order current differential sequence of the current data sequence; the multi-order current differential sequence includes a first-order current differential sequence and a second-order current differential sequence;

[0015] According to the data of the second-order current difference sequence at each moment, the data of the first-order current difference sequence corresponding to the same moment are adjusted to obtain the weighted current change amount corresponding to each moment;

[0016] The weighted current changes at all corresponding times are averaged and normalized to obtain the current fluctuation coefficient of each electrical component at the current time.

[0017] Furthermore, the method for obtaining the weighted current variation includes:

[0018] Calculate the square of the data of the second-order current difference sequence at each moment as a weighted value;

[0019] The weighted value and the absolute value of the data corresponding to the first-order current difference sequence at the same time are calculated as the weighted current change at each corresponding same time.

[0020] Furthermore, the method for acquiring the fluctuation distribution characteristics includes:

[0021] For each sampling circuit, the difference of voltage data between adjacent moments within the time neighborhood of the current moment is calculated as the first difference; the average of the first differences between all adjacent moments is calculated as the average voltage change at the current moment;

[0022] At the current moment, the median of the average voltage changes of all sampling circuits in the electrical component is obtained, and the voltage fluctuation degree of each sampling circuit at the current moment is obtained according to the difference between the average voltage change of each sampling circuit and the median and the degree of change of the average voltage change of all sampling circuits; the average voltage change is positively correlated with the voltage fluctuation degree, and the degree of change of the average voltage change is negatively correlated with the voltage fluctuation degree.

[0023] Furthermore, the method for obtaining the failure probability includes:

[0024] The product of the current barrier coefficient, the current fluctuation coefficient and the fluctuation distribution characteristics of the voltage data corresponding to each sampling circuit of each electrical component at the current moment is calculated and normalized to obtain the failure probability of each sampling circuit at the current moment.

[0025] Further, monitoring the electrical components according to the fault probability of each sampling circuit at the current moment includes:

[0026] Calculate the mean value of the failure probability of all sampled circuits in each electrical component at the current moment, and record it as the failure judgment probability of each electrical component at the current moment;

[0027] If the fault judgment probability of each electrical component at the current moment is greater than the preset probability threshold, it is determined that the electrical component has an abnormal fault.

[0028] Furthermore, the method for obtaining the time neighborhood range includes:

[0029] Taking the current moment as the benchmark, the range formed by a preset number of adjacent historical moments is the time neighborhood range of the current moment.

[0030] Furthermore, the method for acquiring the current differential sequence includes:

[0031] The current data sequence is differentially processed to obtain a multi-order current differential sequence of the current data sequence.

[0032] Furthermore, the preset probability threshold is 0.56. The present invention has the following beneficial effects:

[0033] The present invention takes into account that the failure of electrical components is usually related to abnormal changes in current and voltage. In order to accurately analyze the health status of electrical components, the current data of the electrical components at each moment within the time neighborhood of the current moment and the voltage data of the sampling circuit in the electrical components are obtained; according to the current data distribution of the electrical components at the current moment, the current barrier coefficient of each electrical component at the current moment is obtained, and the degree of obstruction of the current inside the electrical component is reflected by analyzing the distribution state of the current of the electrical components at different moments; according to the change trend of the current data of each electrical component within the time neighborhood of the current moment, the current fluctuation coefficient of each electrical component at the current moment is obtained, and the degree of change of the current data of the electrical component at the current moment is quantified, which is helpful for subsequent analysis of the degree of instability or potential failure of the electrical components; according to the current barrier coefficient and current fluctuation coefficient of each electrical component at the current moment and the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood, the failure probability of each sampling circuit at the current moment is obtained, and the changes of the current data and the voltage data are analyzed comprehensively to comprehensively evaluate the degree of failure of each electrical component; according to the failure probability of each sampling circuit at the current moment, the electrical components are monitored, the electrical components with abnormal failures are accurately judged, and the potential failures are discovered and handled in time. The present invention improves the accuracy of abnormal fault monitoring by analyzing the possibility of abnormal faults occurring in each electrical component. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A flowchart of a fault diagnosis method for a photovoltaic combiner box provided by an embodiment of the present invention;

[0036] Figure 2 A flow chart of a method for obtaining a current fluctuation coefficient provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the fault diagnosis method for a photovoltaic combiner box proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0039] A specific scheme of a fault diagnosis method for a photovoltaic combiner box provided by the present invention is described in detail below with reference to the accompanying drawings.

[0040] See also Figure 1 , which shows a flow chart of a fault diagnosis method for a photovoltaic combiner box provided by an embodiment of the present invention, and the specific method includes:

[0041] Step S1: Acquire the current data of the electrical component and the voltage data on the sampling circuit in the electrical component at each moment within the time neighborhood of the current moment.

[0042] When the photovoltaic combiner box is in operation, the sensor will collect various data of the electrical components in the photovoltaic combiner box and store them in the database. In the embodiment of the present invention, for the photovoltaic combiner box, the electrical components are components used in the power generation process to realize certain functions, such as DC circuit breakers, which serve as output control devices of the photovoltaic combiner box; in order to timely monitor the aging of devices and component damage in the electrical components, avoid losses and safety risks caused by failures, improve the reliability of the power generation system, and ensure the long-term stable operation of the system, it is necessary to analyze the performance of various electrical parameters of the electrical components; first, considering that when multiple electrical components in the photovoltaic combiner box are installed and distributed, different electrical components are often connected in parallel, and one electrical component corresponds to multiple sampling circuits; because different sampling circuits in the electrical components are connected in series, the current of the corresponding sampling circuits is the same, and the current data of each electrical component is obtained based on the current sensor in the electrical component; the voltage data on different sampling circuits in different electrical components is obtained based on the voltage sensor; the current data of the electrical component and the voltage data of the sampling circuit in the electrical component at each moment within the time neighborhood of the current moment are obtained.

[0043] It should be noted that, in one embodiment of the present invention, the number of electrical components is 5, the number of sampling circuits in each electrical component is 10, the time interval is 5s, and the method for obtaining the time neighborhood range includes: taking the current moment as a reference, and the range formed by a preset number of adjacent historical moments is the time neighborhood range of the current moment; the preset number is set to 499, and a total of 500 moments of data are obtained for analysis; in other embodiments of the present invention, the number of electrical components, the number of sampling circuits, the time interval, the preset number and the size of the time neighborhood range of the current moment can be set according to the specific circumstances, and are not limited or elaborated here.

[0044] Step S2: According to the current data distribution of the electrical components at the current moment, the current barrier coefficient of each electrical component at the current moment is obtained; according to the change trend of the current data of each electrical component within the time neighborhood at the current moment, the current fluctuation coefficient of each electrical component at the current moment is obtained.

[0045] Since the sampling circuits in electrical components are connected in series, if a fault occurs in the sampling circuit and the current decreases, the current data of the entire electrical component will be affected, and the smaller the current data is compared to the normal current data; through current analysis, abnormal currents that may exist in electrical components can be identified. These abnormal currents may indicate that the flow of current is hindered by aging, short circuit, open circuit or other potential faults of electrical components, resulting in system performance degradation, and the larger the current barrier coefficient; by analyzing the degree of change in the current data of electrical components over a period of time, the failure trend of electrical components can be indicated. The greater the degree of change, the greater the current fluctuation coefficient, which means that the electrical component has a safety risk or is about to fail; comprehensive analysis of the current barrier coefficient and the current fluctuation coefficient can better understand the performance of electrical components under dynamic working conditions, and understand the safety and stability of power generation.

[0046] By analyzing the current data distribution, we can reveal the working status of different electrical components at certain moments and understand the working characteristics of electrical components; the current barrier coefficient is used to indicate the degree of obstruction of the current flow of electrical components at certain moments. The higher the current barrier coefficient, the greater the obstruction to the current flow, which means that the performance of the electrical component is degraded or there is a fault. Therefore, according to the current data distribution of the electrical components at the current moment, the current barrier coefficient of each electrical component at the current moment is obtained.

[0047] Preferably, in one embodiment of the present invention, the method for obtaining the current barrier coefficient includes:

[0048] At the current moment, the average value of the current data of all electrical components is calculated as the current average value;

[0049] According to the difference between the current mean and the current data of each electrical component, as well as the degree of fluctuation of the current data of all electrical components, the current barrier coefficient of each electrical component at the current moment is obtained. The difference is positively correlated with the current barrier coefficient, and the degree of fluctuation is negatively correlated with the current barrier coefficient. Among them, the positive correlation relationship means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be a multiplication relationship, an addition relationship, or the power of an exponential function, which is determined by actual application; the negative correlation relationship means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by actual application.

[0050] In one embodiment of the present invention, the formula of the current barrier coefficient is expressed as:

[0051] ;

[0052] in, Indicates the current Time next Electrical components The current barrier coefficient of Indicates the current The average current of all electrical components at the moment; Indicates the current Time next Electrical components Current data of Indicates the current The degree of fluctuation of the current data of all electrical components at a given moment.

[0053] In the formula for the current barrier coefficient, Indicates the current The average current of all electrical components at the moment Electrical components The difference between the current data of Electrical components The smaller the current data, the greater the current barrier coefficient, and the more abnormal the electrical components are; on the contrary, the smaller the difference, the Electrical components The closer the current data is to the current mean, the smaller the current barrier coefficient is, and the smaller the possibility of abnormality in electrical components is; Indicates the current The average current of all electrical components at the moment Electrical components The ratio of the difference between the current data and the degree of fluctuation, that is, the current difference between the electrical components is quantified. When the degree of fluctuation is smaller, the fluctuation range of the current data between the electrical components is smaller; Electrical components The smaller the current data is, the greater the difference between the current mean values ​​of other electrical components is, the greater the current difference between electrical components is, and the more likely the current data of the corresponding electrical component is abnormal.

[0054] It should be noted that, in one embodiment of the present invention, the degree of fluctuation is characterized by calculating the variance. The larger the variance, the greater the degree of fluctuation, and the smaller the variance, the smaller the degree of fluctuation. In other embodiments of the present invention, the range or mean deviation may also be calculated to characterize the degree of fluctuation. The specific means are technical means well known to those skilled in the art and will not be elaborated here.

[0055] In the photovoltaic combiner box, due to abnormal faults in electrical components, the transmission of current is likely to be intermittent, and the current data in the electrical components will have large fluctuations; the larger and more frequent the fluctuations in current data, the greater the safety risk of the electrical components, and the more likely the electrical components will have abnormal faults; therefore, the current fluctuation coefficient of the electrical components at the current moment is obtained based on the change trend of the current data of the electrical components within the time neighborhood at the current moment.

[0056] Preferably, in one embodiment of the present invention, the method for obtaining the current fluctuation coefficient can be found in Figure 2 , which shows a flow chart of a method for obtaining a current fluctuation coefficient provided by an embodiment of the present invention, the method comprising:

[0057] Step S201: constructing a current data sequence of each electrical component within a time neighborhood at the current moment, and obtaining a multi-order current differential sequence of the current data sequence; the multi-order current differential sequence includes a first-order current differential sequence and a second-order current differential sequence.

[0058] When an electrical component has an abnormal fault, the current will change over time. The differential sequence can capture the rate and trend of current change and reduce the impact of noise in the original data. Among them, the first-order current differential represents the change in current value at adjacent moments, reflecting the rate of current change. By analyzing the first-order differential sequence, we can understand the current change characteristics of the electrical component at different moments. The second-order current differential is the difference of the first-order differential, which represents the change in the current change rate and can reveal the acceleration information of the current change, which helps to understand the dynamic performance of electrical components and detect abnormal behavior.

[0059] It should be noted that, in one embodiment of the present invention, the method for obtaining the current differential sequence includes: performing differential processing on the current data sequence to obtain a multi-order current differential sequence of the current data sequence. The specific current differential sequence is a technical means well known to those skilled in the art and will not be described in detail here.

[0060] Step S202: adjusting the data of the first-order current difference sequence at the same time according to the data of the second-order current difference sequence at each time, and obtaining the weighted current variation at each time.

[0061] In some cases, the first-order current differential sequence may be affected by noise or other interference factors, resulting in inaccurate data. By introducing the second-order current differential sequence for adjustment, we can more comprehensively understand the dynamic characteristics of current changes and thus more accurately describe the performance of electrical components.

[0062] Preferably, in one embodiment of the present invention, the method for obtaining the weighted current variation includes:

[0063] The square of the data of the second-order current difference sequence at each moment is calculated as the weighted value; the absolute value of the weighted value and the data of the first-order current difference sequence at the same moment is calculated as the weighted current change at each corresponding moment.

[0064] In one embodiment of the present invention, the formula for the weighted current variation is expressed as:

[0065] ;

[0066] in, Indicates the current The serial number of the adjacent historical moment of the moment; Indicates the current The moment adjacent historical moments; Indicates Time next Electrical components The weighted current change of Indicates Electrical components The second-order current difference sequence is The data value at the moment; Indicates Electrical components The first-order current difference sequence is The data value at the moment.

[0067] In the formula for weighted current change, It means calculating the square of the data of the second-order current difference sequence at each moment as the weighted value; the absolute value of the data of the first-order current difference sequence at the corresponding moment is the change of the current data. The greater the change of the current data, the greater the change of the second-order current difference sequence at the first moment. The larger the data value at a certain moment, the faster the current data changes at the corresponding moment, the larger the current change is adjusted, and the larger the weighted current change is.

[0068] It should be noted that, in one embodiment of the present invention, Electrical components The first-order current difference sequence is Data value at the moment ;No. Electrical components The second-order current difference sequence is Data value at the moment In other embodiments of the present invention, other positive correlation mapping methods such as addition method can also be used to construct the first-order current difference sequence and the second-order current difference sequence in the first The larger the data value at a moment is, the greater the positive correlation is, and the larger the weighted current change is. The specific means are well known to those skilled in the art and will not be elaborated here.

[0069] Step S203: averaging all weighted current changes at the same time and normalizing them to obtain the current fluctuation coefficient of each electrical component at the current time.

[0070] In one embodiment of the present invention, the formula for the current fluctuation coefficient is expressed as:

[0071] ;

[0072] in, Indicates the current Time next Electrical components The current fluctuation coefficient; Indicates the current The serial number of the adjacent historical moment of the moment; Indicates the current The moment adjacent historical moments; Indicates Time next Electrical components The weighted current change of Indicates the number of moments within the time neighborhood; represents the logistic function.

[0073] In the formula for the current fluctuation coefficient, the Function pair Perform normalized mapping, It means to find the average of the weighted current changes at all corresponding moments. The larger the average, the larger the weighted current change at each corresponding moment, the larger and faster the current change trend of the electrical component, the larger the current fluctuation coefficient, and the more likely it is caused by an abnormal fault.

[0074] The current obstacle coefficient reflects the degree of influence of certain factors that hinder the normal flow of current in the electrical component. The larger the current obstacle coefficient, the greater the degree of influence of the factors that hinder the normal flow of current, and the more likely it is that an abnormal fault will exist; the current fluctuation coefficient reflects the fluctuation of the current data of the electrical component. The larger the current fluctuation coefficient, the more likely it is that the current will fluctuate greatly, and the more likely it is that an abnormal fault will exist; but since the sampling circuits of the same electrical component are connected in series and the currents between different sampling circuits are the same, it is impossible to accurately judge the state of the electrical component based solely on current analysis.

[0075] Step S3: Obtain the fault probability of each sampling circuit at the current moment according to the current barrier coefficient and current fluctuation coefficient of each electrical component at the current moment and the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood.

[0076] Taking into account that abnormal faults affect the current of the sampling circuit as well as the voltage, the voltage changes between normal sampling circuits are similar, and the voltage changes of faulty sampling circuits are different from those of normal sampling circuits. Therefore, the fluctuation distribution characteristics of the voltage data of each sampling circuit are analyzed to reflect the voltage changes of the sampling circuit; the analysis of the changes in current data and voltage data is combined to comprehensively evaluate the degree of fault in each sampling circuit; therefore, the failure probability of each sampling circuit at the current moment is obtained based on the current barrier coefficient, current fluctuation coefficient of each electrical component and the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood.

[0077] Preferably, in one embodiment of the present invention, the method for acquiring the fluctuation distribution characteristics includes:

[0078] For each sampling circuit, the difference of voltage data between adjacent moments within the time neighborhood of the current moment is calculated as the first difference; the average of the first differences between all adjacent moments is calculated as the average voltage change at the current moment;

[0079] At the current moment, the median of the average voltage changes of all sampling circuits in the electrical component is obtained, and the voltage fluctuation degree of each sampling circuit at the current moment is obtained according to the difference between the average voltage change of the sampling circuit and the median and the degree of change of the average voltage change of all sampling circuits; the difference between the average voltage change and the median is positively correlated with the voltage fluctuation degree, and the degree of change of the average voltage change is negatively correlated with the voltage fluctuation degree. Among them, the positive correlation relationship indicates that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be a multiplication relationship, an addition relationship, and the power of an exponential function, which is determined by actual application; the negative correlation relationship indicates that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by actual application.

[0080] Preferably, in one embodiment of the present invention, the method for obtaining the failure probability includes:

[0081] The product of the current barrier coefficient, the current fluctuation coefficient of each electrical component and the voltage fluctuation degree of each sampling circuit at the current moment is calculated and normalized to obtain the failure probability of each sampling circuit at the current moment.

[0082] In one embodiment of the present invention, the formula for the failure probability is expressed as:

[0083] ;

[0084] ;

[0085] in, Indicates the current Time next The electrical components Sampling circuit The probability of failure; Indicates the current Time next Electrical components The current barrier coefficient of Indicates the current Time next Electrical components The current fluctuation coefficient; Indicates the current Time next The electrical components Sampling circuit The degree of voltage fluctuation; Indicates the current Time next The electrical components Sampling circuit The average voltage change; Indicates the current Time next Electrical components The median of the average voltage change of all sampling circuits; Indicates the current Time next Electrical components The degree of change in the average voltage change of all sampling circuits; Represents the normalization function.

[0086] In the formula for failure probability, Indicates the current Time next The electrical components Sampling circuit The difference between the average voltage change of the sampled circuits and the median of the average voltage change of all sampled circuits indicates the difference between the average voltage change of the sampled circuits and the median of the average voltage change of all sampled circuits. Sampling circuit Compared with the deviation of the average voltage change of other sampling circuits, the greater the difference, the greater the deviation of the average voltage change of the electrical component. Sampling circuit The greater the deviation between the average voltage change and other sampling circuits, the more likely the sampling circuit is abnormal; Indicates the first Sampling circuit In the current The range of the average voltage change at the moment is used to Quantify; Represents sampling circuit The smaller the range of voltage fluctuation, the more consistent the average voltage change between the sampling circuits. The greater the deviation between the average voltage change and other sampling circuits, the greater the deviation of the sampling circuit The greater the voltage fluctuation, the more likely it is that there will be an abnormal fault; combined with the current Time next Electrical components The larger the current barrier coefficient, the greater the current difference between an electrical component and other electrical components. When the current fluctuation coefficient is larger, the faster the current of the electrical component changes, the greater the possibility of abnormal faults and the greater the probability of faults.

[0087] It should be noted that, in one embodiment of the present invention, the degree of change of the average voltage change of all sampling circuits can be characterized by calculating the variance of the average voltage change of all sampling circuits. The larger the variance, the greater the degree of change, and the greater the fluctuation of the average voltage change between the sampling circuits. The smaller the variance, the smaller the degree of change, and the smaller the fluctuation of the average voltage change between the sampling circuits. In other embodiments of the present invention, the current barrier coefficient, the current fluctuation coefficient, and the voltage fluctuation degree of each sampling circuit can be normalized and then added together, and other basic mathematical operation methods can be used to construct a positive correlation relationship in which the larger each part is, the greater the probability of failure. The specific means are technical means well known to those skilled in the art and will not be elaborated here.

[0088] Step S4: monitor the electrical components according to the failure probability of each sampling circuit at the current moment.

[0089] Failure probability provides a more comprehensive understanding of the performance and failure conditions of electrical components, timely detection and treatment of electrical components with potential failures, and avoids the impact of failures on the entire power generation system, thereby improving the reliability and stability of the system. Abnormal monitoring of electrical components is performed based on the failure probability of each sampling circuit at the current moment.

[0090] Preferably, in one embodiment of the present invention, monitoring the electrical components according to the failure probability of each sampling circuit at the current moment includes:

[0091] Calculate the mean value of the failure probability of all sampled circuits in each electrical component at the current moment, and record it as the failure judgment probability of each electrical component at the current moment;

[0092] If the fault judgment probability of each electrical component at the current moment is greater than the preset probability threshold, it is determined that the electrical component has an abnormal fault.

[0093] It should be noted that, in one embodiment of the present invention, the preset probability threshold is 0.56; in other embodiments of the present invention, the size of the preset probability threshold can be set according to the specific situation, which is not limited or elaborated here.

[0094] It should be noted that after determining that an electrical component has an abnormal fault, the corresponding position coordinates and serial number can be marked and sent to the control platform together with the alarm information to further notify the staff to investigate and repair it, so as to avoid energy loss caused by electrical component failure and time loss caused by system downtime, and ensure the stable operation of the power generation system.

[0095] In summary, the present invention obtains the current data of the electrical components at each moment within the time neighborhood of the current moment and the voltage data of the sampling circuit in the electrical components; obtains the current barrier coefficient of each electrical component at the current moment according to the current data distribution of the electrical components at the current moment; obtains the current fluctuation coefficient of each electrical component at the current moment according to the change trend of the current data of the electrical components within the time neighborhood of the current moment; obtains the failure probability of each sampling circuit at the current moment according to the current barrier coefficient, current fluctuation coefficient of each electrical component and the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood at the current moment; and performs abnormal monitoring on the electrical components. The present invention improves the accuracy of abnormal fault monitoring by analyzing the possibility of abnormal faults in each electrical component.

[0096] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0097] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A fault diagnosis method for a photovoltaic combiner box, characterized in that: The method comprises: Obtaining the current data of the electrical component and the voltage data of the sampling circuit in the electrical component at each moment within the time neighborhood of the current moment; According to the current data distribution of the electrical components at the current moment, the current barrier coefficient of each electrical component at the current moment is obtained; according to the change trend of the current data of each electrical component within the time neighborhood at the current moment, the current fluctuation coefficient of each electrical component at the current moment is obtained; Obtaining the failure probability of each sampling circuit at the current moment according to the current barrier coefficient of each electrical component at the current moment, the current fluctuation coefficient, and the fluctuation distribution characteristics of the voltage data of each sampling circuit within the corresponding time neighborhood; Monitoring electrical components according to the failure probability of each sampling circuit at the current moment; The method for obtaining the current barrier coefficient includes: At the current moment, the average value of the current data of all electrical components is calculated as the current average value; The current barrier coefficient of each electrical component at the current moment is obtained according to the difference between the current mean and the current data of each electrical component, as well as the fluctuation degree of the current data of all electrical components. The difference is positively correlated with the current barrier coefficient, and the fluctuation degree is negatively correlated with the current barrier coefficient. The method for obtaining the current fluctuation coefficient includes: Constructing a current data sequence of each electrical component within a time neighborhood at the current moment, and obtaining a multi-order current differential sequence of the current data sequence; the multi-order current differential sequence includes a first-order current differential sequence and a second-order current differential sequence; According to the data of the second-order current difference sequence at each moment, the data of the first-order current difference sequence corresponding to the same moment are adjusted to obtain the weighted current change amount corresponding to each moment; The weighted current changes at the same time are averaged and normalized to obtain the current fluctuation coefficient of each electrical component at the current time; The method for obtaining the weighted current variation comprises: Calculate the square of the data of the second-order current difference sequence at each moment as a weighted value; Calculate the absolute value of the weighted value and the first-order current difference sequence corresponding to the data at the same time as the weighted current change at each corresponding time; The method for acquiring the current differential sequence includes: The current data sequence is differentially processed to obtain a multi-order current differential sequence of the current data sequence.

2. A fault diagnosis method for a photovoltaic combiner box according to claim 1, characterized in that: The method for acquiring the fluctuation distribution characteristics comprises: For each sampling circuit, the difference of voltage data between adjacent moments within the time neighborhood of the current moment is calculated as the first difference; the average of the first differences between all adjacent moments is calculated as the average voltage change at the current moment; At the current moment, the median of the average voltage changes of all sampling circuits in the electrical component is obtained, and the voltage fluctuation degree of each sampling circuit at the current moment is obtained according to the difference between the average voltage change of each sampling circuit and the median and the degree of change of the average voltage change of all sampling circuits; the average voltage change is positively correlated with the voltage fluctuation degree, and the degree of change of the average voltage change is negatively correlated with the voltage fluctuation degree.

3. A fault diagnosis method for a photovoltaic combiner box according to claim 2, characterized in that: The method for obtaining the failure probability includes: The product of the current barrier coefficient, the current fluctuation coefficient and the fluctuation distribution characteristic of the voltage data corresponding to each sampling circuit of each electrical component at the current moment is calculated and normalized to obtain the failure probability of each sampling circuit at the current moment.

4. A fault diagnosis method for a photovoltaic combiner box according to claim 1, characterized in that: The monitoring of electrical components according to the fault probability of each sampling circuit at the current moment includes: Calculate the mean value of the failure probability of all sampling circuits in each electrical component at the current moment, and record it as the failure judgment probability of each electrical component at the current moment; If the fault judgment probability of each electrical component at the current moment is greater than the preset probability threshold, it is determined that the electrical component has an abnormal fault.

5. A fault diagnosis method for a photovoltaic combiner box according to claim 1, characterized in that: The method for obtaining the time neighborhood range includes: Taking the current moment as the benchmark, the range formed by a preset number of adjacent historical moments is the time neighborhood range of the current moment.

6. A fault diagnosis method for a photovoltaic combiner box according to claim 4, characterized in that: The preset probability threshold is 0.56.

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