Photovoltaic inverter string abnormity diagnosis and disposal method and device based on dispersion rate

Abstract

The invention relates to a photovoltaic inverter string abnormity diagnosis and disposal method and device based on a dispersion rate. The photovoltaic inverter string abnormity diagnosis and disposal method based on the dispersion rate comprises the following steps: acquiring the current dispersion rate and / or the voltage dispersion rate of each string in an abnormal inverter at each moment; based on the current dispersion rate and / or the voltage dispersion rate of each group string in the abnormal inverter at each moment, determining the daily-level current dispersion rate and / or the daily-level voltage dispersion rate of each group string in the abnormal inverter; determining an abnormal string in the abnormal inverter based on the daily-level current dispersion rate and / or daily-level voltage dispersion rate of each string in the abnormal inverter; based on the abnormal string root cause diagnosis model, the abnormal string is diagnosed, the string fault type of the abnormal string is determined, the abnormal inverter can be determined more accurately in a large number of inverters, and the abnormal string can be determined in a large number of strings.

Description

Technical Field

[0001] The present disclosure relates to the technical field of integrated energy systems, and in particular to a method for diagnosing and handling abnormalities of photovoltaic inverter strings based on discrete rate, a device for diagnosing and handling abnormalities of photovoltaic inverter strings based on discrete rate, a storage medium and a server. Background Art

[0002] An inverter is a power electronic device whose main function is to convert DC power (such as power provided by batteries and storage bottles) into AC power (generally 220V, 50Hz sine wave). The inverter consists of an inverter bridge, control logic and filter circuits, and is widely used in various occasions that require AC power supply. However, when the inverter is used, it may fail. Sometimes there are many inverters, and it is necessary to determine which inverter has a problem, which string in the inverter has a problem, etc., so as to facilitate the maintenance of the faulty inverter. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure are intended to provide a method for diagnosing and handling abnormalities of a photovoltaic inverter string based on discrete rate, a device for diagnosing and handling abnormalities of a photovoltaic inverter string based on discrete rate, a storage medium and a server.

[0004] The technical solution of the present disclosure is achieved as follows:

[0005] In a first aspect, the present disclosure provides a method for diagnosing and handling abnormalities of photovoltaic inverter strings based on discrete rate.

[0006] The embodiment of the present disclosure provides a method for diagnosing and handling abnormalities of photovoltaic inverter strings based on discrete rate, including:

[0007] Obtain the current discrete rate and voltage discrete rate of each inverter at each moment;

[0008] Determine the daily discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment;

[0009] Based on the daily discrete rate of each inverter, an abnormal inverter among the inverters is determined;

[0010] Obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0011] Determine the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0012] Determining the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or the daily voltage discrete rate of each string in the abnormal inverter;

[0013] Based on the abnormal string root cause diagnosis model, the abnormal strings in the abnormal inverter are diagnosed to determine the string fault type of the abnormal strings, and based on the string fault type of the abnormal strings, a disposal plan corresponding to the string fault type of the abnormal strings is determined; wherein the abnormal string root cause diagnosis model includes a plurality of abnormal states of abnormal strings and the string fault types corresponding to the abnormal states.

[0014] In some embodiments, the step of obtaining the current discrete rate and the voltage discrete rate of each inverter at each moment includes:

[0015] Get the current discrete rate ρ of a single inverter at each moment 流 :

[0016] Among them, n is the number of valid strings, i represents the i-th string, x i is the effective current value of the effective string at the i-th moment, and x is the current mode value of the current values ​​collected by all strings at all times;

[0017] Get the voltage discrete rate ρ of a single inverter at each moment 压 :

[0018] Where n is the number of valid strings, i represents the i-th string, y i is the effective voltage value of the effective string at the i-th moment, and y is the voltage mode value of the voltage values ​​collected by all strings at all times.

[0019] In some embodiments, determining the daily discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment includes:

[0020] Determine the comprehensive discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment;

[0021] Based on the comprehensive discrete rate of each inverter, the daily discrete rate of each inverter is determined.

[0022] In some embodiments, determining the daily discrete rate of each inverter based on the comprehensive discrete rate of each inverter includes: ρ i is the comprehensive discrete rate of a single inverter at each i-th moment, ρ 日 is the daily discrete rate of a single inverter, and m is the number of measurements at all times within the effective time range of a single inverter.

[0023] In some embodiments, the step of obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes:

[0024] ρ 串流 =(I 实时 -I 众数 ) / I 众数 *100%; where ρ 串流 is the current discrete rate of the target string in the abnormal inverter at the target time, I 实时 is the current of the target string in the abnormal inverter at the target time, I 众数 is the mode of current of the abnormal inverter at all times;

[0025] ρ 串压 =(V 实时 -V 众数 ) / V 众数 *100%; where ρ 串压 is the voltage discrete rate of the target string in the abnormal inverter at the target time, V 实时 is the voltage of the target string in the abnormal inverter at the target time, V 众数 is the voltage mode of the abnormal inverter at all times.

[0026] In some embodiments, determining the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes:

[0027] Among them, ρ 日串流 is the daily current discrete rate of the target string in the abnormal inverter, f1 is the number of valid string current values, j represents the jth value of the valid string current value, x j日串流 is the current value collected at the jth moment, x 日串流 is the average value of the mode of current values ​​collected at all times; x 流众 is the mode of current at each moment;

[0028] Among them, ρ 日串压 is the daily voltage discrete rate of the target string in the abnormal inverter, f2 is the number of valid string voltage values, k represents the kth value of the valid string effective voltage value, x k日串压 is the voltage value collected at the kth moment, x 日串压 is the average value of the mode of voltage values ​​collected at all times; x 压众 is the voltage mode at each moment.

[0029] In some embodiments, the abnormal states of the multiple abnormal strings and the string fault types corresponding to the abnormal states include:

[0030] The first abnormal state of the abnormal string is that the current value is lower than the first threshold value within a predetermined time period, wherein the string fault type corresponding to the first abnormal state is a zero current string;

[0031] The second abnormal state of the abnormal string is that the hourly string current discrete rate monitored every day is a positive deviation, and the discrete rate is greater than 100%, or the hourly string voltage discrete rate every day is a positive deviation, and the discrete rate is greater than 100%, wherein the string fault type corresponding to the second abnormal state is an extremely large abnormal constant value string;

[0032] The third abnormal state of the abnormal string is that the similarity of the continuous periodic change of the hourly current discrete rate of the string reaches the second threshold, and when the string is blocked, the current discrete rate is negative, and after the shadow gradually disappears, the current discrete deviation rate gradually tends to normal; wherein, the string fault type corresponding to the third abnormal state is the shadow-blocked string;

[0033] The fourth abnormal state of the abnormal string is that the voltage discrete rate of the string changes suddenly from the normal discrete rate to the abnormal discrete rate; wherein the string fault type corresponding to the fourth abnormal state is a component damaged string;

[0034] The fifth abnormal state of the abnormal string is that if the voltage dispersion rate of the string is abnormal every hour of the day, the corresponding string current dispersion rate change is normal; wherein the string fault type corresponding to the fifth abnormal state is a terminal loose string;

[0035] The sixth abnormal state of the abnormal string is that the voltage and current discrete rates of the string change at the same frequency every day, and the linear regression method of the voltage and current discrete rates is adopted, and the trend shows a linear relationship; wherein the string fault type corresponding to the sixth abnormal state is a component mismatch string;

[0036] The seventh abnormal state of the abnormal string is that if the daily discrete rate of the string presents a linear change trend with an annual cycle, and the daily discrete rate increases daily; wherein, the string fault type corresponding to the seventh abnormal state is an attenuation abnormal string.

[0037] In a second aspect, the present disclosure provides a photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate, comprising:

[0038] A first discrete rate acquisition module is used to acquire the current discrete rate and voltage discrete rate of each inverter at each moment;

[0039] A first daily discrete rate determination module, configured to determine the daily discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment;

[0040] An abnormal inverter determination module, used for determining an abnormal inverter among the inverters based on the daily discrete rate of each inverter;

[0041] A second discrete rate acquisition module is used to acquire the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0042] A second daily discrete rate determination module is used to determine the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0043] An abnormal string determination module is used to determine the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter;

[0044] A string fault diagnosis module is used to diagnose the abnormal strings in the abnormal inverter based on an abnormal string root cause diagnosis model, determine the string fault type of the abnormal strings, and determine a treatment plan corresponding to the string fault type of the abnormal strings based on the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes a plurality of abnormal states of abnormal strings and the string fault types corresponding to the abnormal states.

[0045] In a third aspect, the present disclosure provides a computer-readable storage medium on which a discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program is stored. When the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program is executed by a processor, the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling method described in the first aspect above is implemented.

[0046] In a fourth aspect, the present disclosure provides a server comprising a memory, a processor, and a discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program stored in the memory and executable on the processor, wherein when the processor executes the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program, the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling method described in the first aspect above is implemented.

[0047] According to the embodiment of the present disclosure, a method for diagnosing and handling abnormal photovoltaic inverter strings based on discrete rate includes: obtaining the current discrete rate and voltage discrete rate of each inverter at each moment; determining the daily discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment; determining the abnormal inverter in the inverter based on the daily discrete rate of each inverter; obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; determining the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; determining the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter; diagnosing the abnormal strings in the abnormal inverter based on the abnormal string root cause diagnosis model to determine the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes abnormal states of multiple abnormal strings and string fault types corresponding to the abnormal states. In the present application, when determining the abnormal inverter, a combination of current discrete rate and voltage discrete rate is adopted, which is conducive to more accurately determining the abnormal inverter among a large number of inverters. At the same time, the abnormal string is determined by the daily current discrete rate and daily voltage discrete rate of the string of the abnormal inverter, which is conducive to determining the abnormal string among a large number of strings.

[0048] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of a method for diagnosing and handling abnormality of a photovoltaic inverter string based on discrete rate according to an exemplary embodiment;

[0050] Figure 2 The abnormal string type diagnosis process is shown according to an exemplary embodiment. Figure 1 ;

[0051] Figure 3 The abnormal string type diagnosis process is shown according to an exemplary embodiment. Figure 2 ;

[0052] Figure 4 is a flowchart of abnormal string handling according to an exemplary embodiment;

[0053] Figure 5 The present invention is a schematic structural diagram of a photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate according to an exemplary embodiment. DETAILED DESCRIPTION

[0054] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0055] An inverter is a power electronic device whose main function is to convert DC power (such as power provided by batteries and storage bottles) into AC power (generally 220V, 50Hz sine wave). The inverter consists of an inverter bridge, control logic and filter circuit, and is widely used in various occasions that require AC power supply. However, inverters may fail when they are used. Sometimes there are many inverters, and it is necessary to determine which inverter has a problem, which string in the inverter has a problem, etc., in order to repair the faulty inverter. However, the traditional method of troubleshooting abnormal string faults usually requires manual on-site inspection and detection one by one, which is inefficient and inaccurate.

[0056] In view of the above situation, the present disclosure provides a method for diagnosing and handling abnormalities of photovoltaic inverter strings based on discrete rate, which can perform abnormality diagnosis through automatic data collection and intelligent analysis. Figure 1 FIG. 1 is a flow chart of a method for diagnosing and handling abnormal photovoltaic inverter strings based on discrete rate according to an exemplary embodiment. Figure 1 As shown, the photovoltaic inverter string abnormality diagnosis and treatment method based on discrete rate includes:

[0057] Step 10: Obtain the current discrete rate and voltage discrete rate of each inverter at each moment;

[0058] Step 11: Determine the daily discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment;

[0059] Step 12: based on the daily discrete rate of each inverter, determine the abnormal inverter among the inverters;

[0060] Step 13: obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0061] Step 14: determining the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0062] Step 15: determining the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter;

[0063] Step 16: Based on the abnormal string root cause diagnosis model, diagnose the abnormal strings in the abnormal inverter, determine the string fault type of the abnormal strings, and determine a treatment plan corresponding to the string fault type of the abnormal strings based on the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes multiple abnormal states of abnormal strings and the string fault types corresponding to the abnormal states.

[0064] In an exemplary embodiment, the current of each inverter at each moment can be detected in real time by an electronic device. The current discrete rate of each inverter at each moment is determined by the current of each inverter at each moment. The electronic device can be a current transformer. The voltage of each inverter at each moment is detected by an electronic device. The voltage discrete rate of each inverter at each moment is determined by the voltage of each inverter at each moment. The electronic device can be a voltage transformer.

[0065] In an exemplary embodiment, the daily current discrete rate of each string in the abnormal inverter can be determined based on the current discrete rate of each string in the abnormal inverter at each moment, and the daily voltage discrete rate of each string in the abnormal inverter can be determined based on the voltage discrete rate of each string in the abnormal inverter at each moment. When determining the abnormal strings in the abnormal inverter, it can be determined based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter.

[0066] According to the embodiment of the present disclosure, a method for diagnosing and handling abnormal photovoltaic inverter strings based on discrete rate includes: obtaining the current discrete rate and voltage discrete rate of each inverter at each moment; determining the daily discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment; determining the abnormal inverter in the inverter based on the daily discrete rate of each inverter; obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; determining the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; determining the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter; diagnosing the abnormal strings in the abnormal inverter based on the abnormal string root cause diagnosis model to determine the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes abnormal states of multiple abnormal strings and string fault types corresponding to the abnormal states. In the present application, when determining the abnormal inverter, a combination of current discrete rate and voltage discrete rate is adopted, which is conducive to more accurately determining the abnormal inverter among a large number of inverters. At the same time, the abnormal string is determined by the daily current discrete rate and daily voltage discrete rate of the string of the abnormal inverter, which is conducive to determining the abnormal string among a large number of strings.

[0067] In some embodiments, the step of obtaining the current discrete rate and the voltage discrete rate of each inverter at each moment includes:

[0068] Get the current discrete rate ρ of a single inverter at each moment 流 :

[0069] Among them, n is the number of valid strings, i represents the i-th string, x i is the effective current value of the effective string at the i-th moment, and x is the current mode value of the current values ​​collected by all strings at all times;

[0070] Get the voltage discrete rate ρ of a single inverter at each moment 压 :

[0071] Where n is the number of valid strings, i represents the i-th string, y i is the effective voltage value of the effective string at the i-th moment, and y is the voltage mode value of the voltage values ​​collected by all strings at all times.

[0072] In an exemplary embodiment, the current discrete rate ρ of a single inverter at each moment can be obtained by the above method: 流 and the voltage discrete rate ρ of a single inverter at each moment 压 .

[0073] In an exemplary embodiment, determining the daily discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment includes:

[0074] Determine the comprehensive discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment;

[0075] Based on the comprehensive discrete rate of each inverter, the daily discrete rate of each inverter is determined.

[0076] In an exemplary embodiment, the comprehensive discrete rate of each inverter is determined based on the current discrete rate and voltage discrete rate of each inverter at each moment, and the daily discrete rate of each inverter is determined based on the comprehensive discrete rate of each inverter. Then, the abnormal inverter among the inverters is determined by the daily discrete rate of each inverter. In this way, by combining the current discrete rate and the voltage discrete rate, the accuracy of determining the abnormal inverter can be effectively improved compared with a single indicator based on the current discrete rate or the voltage discrete rate.

[0077] In some embodiments, determining the comprehensive discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment includes:

[0078] ρ 综 =ρ 压*W 压 +ρ 流 *W 流 ;

[0079] ρ 综 The comprehensive discrete rate of a single inverter, W 压 is the voltage discrete rate ρ of a single inverter at each moment 压 The corresponding weight, W 流 is the current discrete rate ρ of a single inverter at each moment 流 The corresponding weight.

[0080] In an exemplary embodiment, the comprehensive discreteness of each inverter can be determined by weighting the current discreteness and the voltage discreteness as described above. 压 is 40%, W 流 60%, and so on.

[0081] In some embodiments, determining the daily discrete rate of each inverter based on the comprehensive discrete rate of each inverter includes: ρ i is the comprehensive discrete rate of a single inverter at each i-th moment, ρ 日 is the daily discrete rate of a single inverter, and m is the number of measurements at all times within the effective time range of a single inverter.

[0082] In an exemplary embodiment, the daily discrete rate of a single inverter may be determined by averaging the comprehensive discrete rates of the single inverter at all times within a day.

[0083] In some embodiments, the step of determining an abnormal inverter among the inverters based on the daily discrete rate of each inverter includes:

[0084] According to the daily inverter discrete rate threshold, the threshold level is set to the first level and the second level; wherein the threshold range of the first level includes: 0%-15%; the threshold range of the second level includes: greater than 15%;

[0085] If the daily discrete rate of the target inverter is within the second-level threshold range, the target inverter is located as an abnormal inverter.

[0086] In an exemplary embodiment, the inverter can be divided into the first level and the second level according to the daily discrete rate threshold of the inverter. The first level is a normal inverter, and the second level is an abnormal inverter. When the daily discrete rate of the inverter is within the threshold range of the first level, the inverter is normal; when the daily discrete rate of the inverter is within the threshold range of the second level, the inverter is abnormal. In this way, the abnormal inverter in the inverter can be effectively determined.

[0087] In some embodiments, the step of obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes:

[0088] ρ 串流 =(I 实时 -I 众数 ) / I 众数 *100%; where ρ 串流 is the current discrete rate of the target string in the abnormal inverter at the target time, I 实时 is the current of the target string in the abnormal inverter at the target time, I 众数 is the mode of current of the abnormal inverter at all times;

[0089] ρ 串压 =(V 实时 -V 众数 ) / V 众数 *100%; where ρ 串压 is the voltage discrete rate of the target string in the abnormal inverter at the target time, V 实时 is the voltage of the target string in the abnormal inverter at the target time, V 众数 is the voltage mode of the abnormal inverter at all times.

[0090] In an exemplary embodiment, the current mode can be obtained by using the Pearson mode method. For example, Mo = ξ-3 (ξ-M d );

[0091] Where: Mo refers to the mode value, ξ: refers to the sample mean, that is, the mean of the string current value, M d : The median of the sample values; where the sample mean is: Where (x i ): represents the current value of each string at that moment. At the same time, the values ​​with negative mode, 0, ≤0.25A, and ≥40A are eliminated. Similarly, the voltage mode can also be obtained by the above Pearson mode method.

[0092] In some embodiments, determining the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes:

[0093] Among them, ρ 日串流 is the daily current discrete rate of the target string in the abnormal inverter, f1 is the number of valid string current values, j represents the jth value of the valid string current value, x j日串流 is the current value collected at the jth moment, x 日串流 is the average value of the mode of current values ​​collected at all times; x流众 is the mode of current at each moment;

[0094] Among them, ρ 日串压 is the daily voltage discrete rate of the target string in the abnormal inverter, f2 is the number of valid string voltage values, k represents the kth value of the valid string effective voltage value, x k日串压 is the voltage value collected at the kth moment, x 日串压 is the average value of the mode of voltage values ​​collected at all times; x 压众 is the voltage mode at each moment.

[0095] In an exemplary embodiment, the current discrete rate of each string in the abnormal inverter at each moment can be calculated by the above formula: The daily current discrete rate of each string in the abnormal inverter is obtained; based on the voltage discrete rate of each string in the abnormal inverter at each moment, through the above formula, The daily voltage dispersion rate of each string in the abnormal inverter is determined.

[0096] In some embodiments, the abnormal states of the multiple abnormal strings and the string fault types corresponding to the abnormal states include:

[0097] The first abnormal state of the abnormal string is that the current value is lower than the first threshold value within a predetermined time period, wherein the string fault type corresponding to the first abnormal state is a zero current string;

[0098] The second abnormal state of the abnormal string is that the hourly string current discrete rate monitored every day is a positive deviation, and the discrete rate is greater than 100%, or the hourly string voltage discrete rate every day is a positive deviation, and the discrete rate is greater than 100%, wherein the string fault type corresponding to the second abnormal state is an extremely large abnormal constant value string;

[0099] The third abnormal state of the abnormal string is that the similarity of the continuous periodic change of the hourly current discrete rate of the string reaches the second threshold, and when the string is blocked, the current discrete rate is negative, and after the shadow gradually disappears, the current discrete deviation rate gradually tends to normal; wherein, the string fault type corresponding to the third abnormal state is the shadow-blocked string;

[0100] The fourth abnormal state of the abnormal string is that the voltage discrete rate of the string changes suddenly from the normal discrete rate to the abnormal discrete rate; wherein the string fault type corresponding to the fourth abnormal state is a component damaged string;

[0101] The fifth abnormal state of the abnormal string is that if the voltage dispersion rate of the string is abnormal every hour of the day, the corresponding string current dispersion rate change is normal; wherein the string fault type corresponding to the fifth abnormal state is a terminal loose string;

[0102] The sixth abnormal state of the abnormal string is that the voltage and current discrete rates of the string change at the same frequency every day, and the linear regression method of the voltage and current discrete rates is adopted, and the trend shows a linear relationship; wherein the string fault type corresponding to the sixth abnormal state is a component mismatch string;

[0103] The seventh abnormal state of the abnormal string is that if the daily discrete rate of the string presents a linear change trend with an annual cycle, and the daily discrete rate increases daily; wherein, the string fault type corresponding to the seventh abnormal state is an attenuation abnormal string.

[0104] In an exemplary embodiment, the first abnormal state of the abnormal string is that the current value is lower than the first threshold value within a predetermined time period, wherein the string fault type corresponding to the first abnormal state is a zero current string; wherein the first threshold value may be a value less than 0.2 A. The hourly current discrete rate of the string is diagnosed to be abnormal, and the current value is continuously lower than the threshold value (which may be set to be lower than 0.2 A); if the current value is continuously lower than the threshold value (0.2 A) from the start of the IoT to the diagnosis date, the string is open-circuited.

[0105] In an exemplary embodiment, the second abnormal state of the abnormal string is that the hourly string current discrete rate monitored every day is a positive deviation, and the discrete rate is greater than 100%, or the hourly string voltage discrete rate monitored every day is a positive deviation, and the discrete rate is greater than 100%, wherein the string fault type corresponding to the second abnormal state is an extremely large abnormal constant value string.

[0106] For example, if the periodic range of the hourly discrete rate of the string is continuously abnormal, the hourly discrete rate of the string current is continuously monitored to be a positive deviation, and the discrete rate is greater than 100%, or the hourly discrete rate of the string voltage is a positive deviation, and the discrete rate is greater than 100%, and historical data is consulted, the historical IoT has been abnormally large current until now, and the IoT is connected to the diagnosis day. If the current or voltage is greater than the abnormally large value, then the string is an extremely large abnormal constant value string.

[0107] In an exemplary embodiment, the third abnormal state of the abnormal string is that the similarity of the continuous periodic change of the hourly current discrete rate of the string reaches the second threshold, and when the string is blocked, the current discrete rate is a negative value, and after the shadow gradually disappears, the current discrete deviation rate gradually tends to normal; the string fault type corresponding to the third abnormal state is a shadow-blocked string. For example, the similarity of the continuous periodic change of the hourly current discrete rate of the string reaches the second threshold: based on the characteristics that when the shadow-blocked string appears blocked, the current discrete rate is a negative value, and after the shadow gradually disappears, the current discrete deviation rate gradually tends to normal. Among them, the second threshold can be a value between 10% and 20%.

[0108] In an exemplary embodiment, a correlation algorithm analysis may be used to associate the time from the start of inverter operation to the shutdown time with the change in the sun rise angle, calculate the hourly discrete rate every day (i.e., the following discrete rate formula), set a period range (e.g., set nearly 7 days), and the discrete rate corresponding to the same time period every day reaches the second threshold of similarity, and the trend of the discrete rate deviation rate in the next time period is 0, then the string is a shadow-blocked string;

[0109] The discrete rate formula is: string discrete rate (at each moment) = (real-time current - mode of all string currents) / mode of string current * 100%.

[0110] In an exemplary embodiment, the fourth abnormal state of the abnormal string is that the voltage discrete rate of the string suddenly changes from a normal discrete rate to an abnormal discrete rate, and it is determined that the string has a damaged component; wherein the string fault type corresponding to the fourth abnormal state is a string with damaged components.

[0111] For example, if the voltage dispersion rate of a string changes suddenly from a normal dispersion rate to an abnormal dispersion rate on a certain day, then the string has damaged components.

[0112] In an exemplary embodiment, the fifth abnormal state of the abnormal string is that if the voltage discrete rate of the string is abnormal every hour of the day, and the corresponding string current discrete rate changes normally, then the string is classified as a terminal loose string; wherein the string fault type corresponding to the fifth abnormal state is a terminal loose string.

[0113] For example, if the voltage dispersion rate of a string is abnormal every hour of every day, and the corresponding string current dispersion rate changes without the above regularity, then the string is classified as a loose operator string.

[0114] In an exemplary embodiment, the sixth abnormal state of the abnormal string is that if the voltage and current discrete rates of the string change at the same frequency in the hourly discrete rates of each day, and the trends show a linear relationship using the linear regression method of the voltage and current discrete rates, then it is determined that there are mismatched components in the string, wherein the string fault type corresponding to the sixth abnormal state is a component mismatched string.

[0115] For example, if the voltage and current discrete rates of a string change at the same frequency every hour of each day, and the linear regression method of the voltage and current discrete rates is used, and the trends show a linear relationship, then the string is a mismatched string; wherein time is taken as the x-axis, and the current or voltage discrete rate is taken as Y, the trend is checked, and whether the trend deviation is within the threshold range is calculated; wherein, the trend deviation rate = (current discrete rate - voltage discrete rate) / (voltage discrete rate), and the deviation threshold may be set as an empirical value (e.g., within 10%).

[0116] In an exemplary embodiment, the seventh abnormal state of the abnormal string is that if the daily discrete rate of the string shows a linear change trend with an annual cycle, and the daily discrete rate increases daily, then the string is determined to be an attenuation abnormal string; wherein the string fault type corresponding to the seventh abnormal state is an attenuation abnormal string.

[0117] In an exemplary embodiment, if the daily discrete rate of a string shows a linear change trend with an annual cycle, for example, if the historical current discrete rate increases daily, then the string is an abnormal attenuation string; wherein, the linear change trend: discrete rate deviation rate = [N-day discrete rate - (N-1) daily discrete rate] / (N-1) daily discrete rate; if the discrete rate deviation rate increases day by day, then the string is determined to be an abnormal attenuation string.

[0118] In an exemplary embodiment, the determining, based on the string fault type of the abnormal string, a handling solution corresponding to the string fault type of the abnormal string includes:

[0119] If the abnormal string is an empty branch string in 0 current, the abnormal string is marked as "empty branch or spare string". The abnormal string marked as "empty branch or spare string" does not participate in calculation and diagnosis analysis.

[0120] If the abnormal string is a string that exceeds the abnormal constant value, the system will automatically send it to the IoT platform to perform rate or base conversion correction to complete the closed loop;

[0121] If the abnormal string is any of the following types: shadowed string, damaged component string, loose terminal string, mismatched component string, or abnormal attenuation string, the abnormal string will be automatically converted to defect according to its string type;

[0122] After the defect is detected, the defect database will be linked to the Energy Carbon Intelligent Assistant model to output disposal suggestions for each type of abnormal string, and recommend spare parts and tools to be carried;

[0123] After the defect is transferred, the disposal suggestion content linked to the defect will be automatically converted into a work order, and the scheduling function will be linked to complete the work order distribution.

[0124] The operation and maintenance worker receives the order, performs on-site disposal according to the disposal suggestions and recommended materials for the defect, and submits the work order after the disposal is completed.

[0125] For example, by combining the large model of the Energy Carbon Intelligent Assistant and the expert knowledge model, specific on-site disposal suggestions are given for the diagnosed "0 current, ultra-large abnormal constant value strings, component damaged strings, loose terminal strings, shadow-blocked strings, component mismatch strings, and component attenuation abnormal strings", and the online and offline disposal methods are linked to trigger the system to automatically mark and remove the spare strings of the 0 current strings in the system, and trigger the IoT repair conversion rate for the ultra-large abnormal constant value strings to recalculate and supplement the data. Other abnormal strings that require offline on-site manual disposal are automatically converted into defects, and the operation and maintenance workers accept the orders through automatic dispatching. According to the root cause diagnosed by the system, disposal suggestions, material suggestions and other information, the repair of offline abnormal fault strings is assisted. After submitting the work order, the system re-verifies whether the strings are repaired based on the abnormal diagnosis model, completes the automatic verification and evaluation of the automatic repair effect, and combines the post-evaluation method to analyze the abnormal strings from the diagnosis of the abnormality to the repair, and evaluates the loss of electricity.

[0126] At the same time, after the problem is diagnosed, converted into a defect, and entered into a work order, the diagnosed problem, the treatment, and the post-evaluation results are pushed to the corresponding role through the intelligent assistant, forming a "find the person for the matter" method, improving the execution rate of abnormal treatment in the power plant, improving the treatment efficiency, and improving the management efficiency of the power plant, thereby improving the power generation efficiency of the power plant and ensuring the power plant's profits. Through the collection of IoT data, diagnosis of abnormal problems, analysis of root causes, output of treatment suggestions, and the use of intelligent assistants and work order treatment capabilities, a closed-loop treatment capability is formed.

[0127] Figure 2 The abnormal string type diagnosis process is shown according to an exemplary embodiment. Figure 1 .like Figure 2 As shown in the figure, the abnormal string type diagnosis process includes:

[0128] Step 20, start;

[0129] Step 21: Determine whether the inverter is offline. If the inverter is offline, it will not participate in the diagnosis:

[0130] Step 22: If the inverter is not offline, determine whether the inverter is faulty or shut down. If the inverter is faulty or shut down, do not participate in the diagnosis:

[0131] Step 23: If the inverter is not faulty or shut down, determine whether to locate the abnormal component. If the abnormal component is not located, do not participate in the diagnosis;

[0132] Step 24: If the inverter fails or shuts down, determine whether the irradiance for 30 minutes is greater than 400w / m2;

[0133] Step 25: If the irradiance for 30 minutes is greater than 400w / m2, the diagnosis start time is after the inverter operation start time;

[0134] Step 26: The end time is when the conditions are met before the inverter shutdown time;

[0135] Step 27: The string current discrete rate is abnormal;

[0136] Step 28, determine whether the current value from the start time to the end time of 10 minutes is less than or equal to 0.2A;

[0137] Step 29: If the current value from the start time to the end time is less than or equal to 0.2A for 10 minutes, the string is diagnosed as a zero current string;

[0138] Step 30, check historical data to determine whether the historical IoT has been a zero current string until now;

[0139] Step 31: If the historical IoT has been a 0 current string until now, it is determined to be an invalid string;

[0140] Step 32: If the historical IoT has not always been a zero current string, determine that the string is open-circuited and has a zero current;

[0141] Step 33: If the current value from the start time to the end time is not less than or equal to 0.2A for 10 minutes, determine whether the hourly discrete rate cycle range of the string is continuously abnormal;

[0142] Step 34: If the hourly discrete rate cycle range of the string continues to be abnormal, check the historical data to determine whether the historical IoT has always been abnormally large current; if the historical IoT has not always been abnormally large current, execute step 36;

[0143] Step 35: If the historical IoT current has been abnormally large, it is determined to be an extremely large abnormal value string;

[0144] Step 36: If there is no continuous abnormality in the period range of the hourly discrete rate of the string, determine whether the similarity of the continuous periodic change of the hourly discrete rate of the string current reaches a threshold;

[0145] Step 37: If the similarity of the continuous periodic variation of the hourly current discrete rate of the string reaches a threshold, it is determined to be a shadow-shaded string.

[0146] Figure 3 The abnormal string type diagnosis process is shown according to an exemplary embodiment. Figure 2 .like Figure 3 As shown in the figure, the abnormal string type diagnosis process includes:

[0147] Step 40, start;

[0148] Step 41: Determine whether the inverter is offline. If the inverter is offline, it will not participate in the diagnosis:

[0149] Step 42: If the inverter is not offline, determine whether the inverter is faulty or shut down. If the inverter is faulty or shut down, do not participate in the diagnosis:

[0150] Step 43: If the inverter is not faulty or shut down, determine whether to locate the abnormal component. If the abnormal component is not located, do not participate in the diagnosis;

[0151] Step 44: If the inverter fails or shuts down, determine whether the irradiance for 30 minutes is greater than 400w / m2;

[0152] Step 45: If the irradiance for 30 minutes is greater than 400w / m2, the diagnosis start time is after the inverter operation start time;

[0153] Step 46: The time that satisfies the conditions before the inverter shutdown time is the end time;

[0154] Step 47, determining that the string voltage discrete rate is abnormal;

[0155] Step 48, determining whether the hourly voltage dispersion rate of the string is always abnormal;

[0156] Step 49: If the hourly voltage discrete rate of the string is always abnormal, determine whether the trend of the voltage discrete rate of the string is similar to the trend of the current discrete rate;

[0157] Step 50: If the trend of the voltage discrete rate and the current discrete rate of the string is similar, it is determined to be a component mismatch string;

[0158] Step 51: If the trend of the voltage discrete rate of the string is not similar to that of the current discrete rate, determine whether the voltage discrete rate of the historical day changes from normal to abnormal;

[0159] Step 52: If the historical daily voltage dispersion rate changes from normal to abnormal, it is determined that the component string is damaged;

[0160] Step 53: If the historical daily voltage dispersion rate does not change from normal to abnormal, determine whether the hourly current dispersion rate and voltage dispersion rate of the string change linearly;

[0161] Step 54: If the hourly current discrete rate and voltage discrete rate of the string change linearly, it is determined to be a string with abnormal string attenuation;

[0162] Step 55: If the hourly current discrete rate and voltage discrete rate of the string do not change linearly, it is determined to be another abnormal string;

[0163] Step 56, when determining whether the hourly voltage discrete rate of the string is always abnormal, if the hourly voltage discrete rate of the string is not always abnormal, determining whether the hourly current discrete rate of the string has no similarity;

[0164] Step 57: If the hourly current discrete rates of the strings have no similarity, it is determined that the string terminals are loose.

[0165] Figure 4 FIG. 1 is a flowchart of abnormal string handling according to an exemplary embodiment. Figure 4 As shown in the figure, the abnormal string handling process includes:

[0166] Step 60, start;

[0167] Step 61, determine whether the abnormal string is a zero current empty branch;

[0168] Step 62: If the abnormal string is a 0-current empty branch, the system automatically notes it as an empty string;

[0169] Step 63: If the abnormal string is not a zero current empty branch, the system automatically turns to a defect;

[0170] Step 64: The system automatically transfers the work order;

[0171] Step 65: The operation and maintenance worker accepts the order;

[0172] Step 66: On-site disposal;

[0173] Step 67: Submit verification;

[0174] Step 68, determine whether the abnormal string is restored to check;

[0175] Step 69: If the abnormal string recovers verification, the loss is evaluated;

[0176] Step 70, determining whether the abnormal string is an extremely large abnormal value string;

[0177] Step 71: If the abnormal string is an extremely large abnormal value string, perform IoT multiplier correction.

[0178] In this application, the abnormal string is first determined to be an empty branch string in 0 current. If so, the system automatically marks the string as "empty branch or spare string", and the string will not participate in calculation and diagnosis analysis in the future, and the system automatically closes the loop to deal with the abnormal string.

[0179] Among them, if the abnormal string is judged to be an abnormal constant value string, the system will automatically send it to the IoT platform, and the IoT delivery personnel of the item platform will make a multiplier or base conversion correction to complete the closed loop.

[0180] For other abnormal strings, they are automatically converted to defects according to the type of string abnormality determined and the type of problem of one inverter in one power station. After being converted to defects, the defect library is linked to the large model of the Energy Carbon Intelligent Assistant to output disposal suggestions for each type of abnormal string, and it is recommended to carry spare parts and tools. After being converted to defects, the disposal suggestions linked to the defects are automatically converted to work orders, and the scheduling function is linked to complete the work order distribution.

[0181] The operation and maintenance worker receives the order, performs on-site disposal according to the disposal suggestions and recommended materials for the defect, and submits the work order after the disposal is completed. After the work order is submitted, the system automatically verifies it. Verification after abnormal disposal:

[0182] Automatic system verification: collect one day's IoT data (current, voltage) of the repaired string, and calculate the hourly and daily discrete rates of each string according to the above numbers. If the discrete rate of the string is within the normal threshold level, the string verification passes and the work order is automatically set to the completed status.

[0183] Intelligent push for abnormal string handling: The diagnosed abnormal strings will be pushed daily through the intelligent assistant message push method. For example, the push content is "On ** year ** month ** day, ** inverter, ** inverter, ** power station, ** zero current strings, ** large abnormal value strings, ** component damaged strings were diagnosed, and the work order has been automatically transferred. Please handle it in time, etc." When the work order is completed and the system passes the verification, the verification result will be automatically pushed to realize the "find a person for the matter" method and improve management efficiency.

[0184] The present invention provides a photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate. Figure 5 FIG. 1 is a schematic diagram of a photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate according to an exemplary embodiment. Figure 5 As shown, the photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate includes:

[0185] A first discrete rate acquisition module 40 is used to acquire the current discrete rate and the voltage discrete rate of each inverter at each moment;

[0186] A first daily discrete rate determination module 41 is used to determine the daily discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment;

[0187] An abnormal inverter determination module 42, configured to determine an abnormal inverter among the inverters based on a daily discrete rate of each inverter;

[0188] A second discrete rate acquisition module 43 is used to acquire the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0189] A second daily discrete rate determination module 44 is used to determine the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment;

[0190] An abnormal string determination module 45 is used to determine the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter;

[0191] The string fault diagnosis module 46 is used to diagnose the abnormal strings in the abnormal inverter based on the abnormal string root cause diagnosis model, determine the string fault type of the abnormal strings, and determine the treatment plan corresponding to the string fault type of the abnormal strings based on the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes a plurality of abnormal states of abnormal strings and the string fault types corresponding to the abnormal states.

[0192] In an exemplary embodiment, the current of each inverter at each moment can be detected in real time by an electronic device. The current discrete rate of each inverter at each moment is determined by the current of each inverter at each moment. The electronic device can be a current transformer. The voltage of each inverter at each moment is detected by an electronic device. The voltage discrete rate of each inverter at each moment is determined by the voltage of each inverter at each moment. The electronic device can be a voltage transformer.

[0193] In an exemplary embodiment, the daily current discrete rate of each string in the abnormal inverter can be determined based on the current discrete rate of each string in the abnormal inverter at each moment, and the daily voltage discrete rate of each string in the abnormal inverter can be determined based on the voltage discrete rate of each string in the abnormal inverter at each moment. When determining the abnormal strings in the abnormal inverter, it can be determined based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter.

[0194] According to the photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate according to the embodiment of the present disclosure, it is used to obtain the current discrete rate and voltage discrete rate of each inverter at each moment; based on the current discrete rate and voltage discrete rate of each inverter at each moment, determine the daily discrete rate of each inverter; based on the daily discrete rate of each inverter, determine the abnormal inverter in the inverter; obtain the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment, determine the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter; based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter, determine the abnormal strings in the abnormal inverter; based on the abnormal string root cause diagnosis model, diagnose the abnormal strings in the abnormal inverter and determine the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes abnormal states of multiple abnormal strings and string fault types corresponding to the abnormal states. In the present application, when determining the abnormal inverter, a combination of current discrete rate and voltage discrete rate is adopted, which is conducive to more accurately determining the abnormal inverter among a large number of inverters. At the same time, the abnormal string is determined by the daily current discrete rate and daily voltage discrete rate of the string of the abnormal inverter, which is conducive to determining the abnormal string among a large number of strings.

[0195] In some embodiments, the first discrete rate acquisition module is used to

[0196] Get the current discrete rate ρ of a single inverter at each moment 流 :

[0197] Among them, n is the number of valid strings, i represents the i-th string, x i is the effective current value of the effective string at the i-th moment, and x is the current mode value of the current values ​​collected by all strings at all times;

[0198] Get the voltage discrete rate ρ of a single inverter at each moment 压 :

[0199] Where n is the number of valid strings, i represents the i-th string, y i is the effective voltage value of the effective string at the i-th moment, and y is the voltage mode value of the voltage values ​​collected by all strings at all times.

[0200] In an exemplary embodiment, the current discrete rate ρ of a single inverter at each moment can be obtained by the above method: 流 And the voltage discrete rate ρ of a single inverter at each moment 压 .

[0201] In an exemplary embodiment, the first daily discrete rate determination module is used to

[0202] Determine the comprehensive discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment;

[0203] Based on the comprehensive discrete rate of each inverter, the daily discrete rate of each inverter is determined.

[0204] In an exemplary embodiment, the comprehensive discrete rate of each inverter is determined based on the current discrete rate and voltage discrete rate of each inverter at each moment, and the daily discrete rate of each inverter is determined based on the comprehensive discrete rate of each inverter. Then, the abnormal inverter among the inverters is determined by the daily discrete rate of each inverter. In this way, by combining the current discrete rate and the voltage discrete rate, the accuracy of determining the abnormal inverter can be effectively improved compared with a single indicator based on the current discrete rate or the voltage discrete rate.

[0205] In some embodiments, the first daily discrete rate determination module is used to

[0206] ρ 综 =ρ 压 *W 压 +ρ 流 *W 流 ;

[0207] ρ 综 The comprehensive discrete rate of a single inverter, W 压 is the voltage discrete rate ρ of a single inverter at each moment 压 The corresponding weight, W 流 is the current discrete rate ρ of a single inverter at each moment 流 The corresponding weight.

[0208] In an exemplary embodiment, the comprehensive discreteness of each inverter can be determined by weighting the current discreteness and the voltage discreteness as described above. 压 is 40%, W 流 60%, and so on.

[0209] In some embodiments, determining the daily discrete rate of each inverter based on the comprehensive discrete rate of each inverter includes: ρ i is the comprehensive discrete rate of a single inverter at each i-th moment, ρ 日 is the daily discrete rate of a single inverter, and m is the number of measurements at all times within the effective time range of a single inverter.

[0210] In an exemplary embodiment, the daily discrete rate of a single inverter may be determined by averaging the comprehensive discrete rates of the single inverter at all times within a day.

[0211] In some embodiments, the abnormal inverter determination module is used to

[0212] According to the daily inverter discrete rate threshold, the threshold level is set to the first level and the second level; wherein the threshold range of the first level includes: 0%-15%; the threshold range of the second level includes: greater than 15%;

[0213] If the daily discrete rate of the target inverter is within the second-level threshold range, the target inverter is located as an abnormal inverter.

[0214] In an exemplary embodiment, the inverter can be divided into the first level and the second level according to the daily discrete rate threshold of the inverter. The first level is a normal inverter, and the second level is an abnormal inverter. When the daily discrete rate of the inverter is within the threshold range of the first level, the inverter is normal; when the daily discrete rate of the inverter is within the threshold range of the second level, the inverter is abnormal. In this way, the abnormal inverter in the inverter can be effectively determined.

[0215] In some embodiments, the step of obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes:

[0216] ρ 串流 =(I 实时 -I 众数 ) / I 众数 *100%; where ρ 串流 is the current discrete rate of the target string in the abnormal inverter at the target time, I 实时 is the current of the target string in the abnormal inverter at the target time, I 众数 is the mode of current of the abnormal inverter at all times;

[0217] ρ 串压 =(V 实时 -V 众数 ) / V 众数 *100%; where ρ 串压 is the voltage discrete rate of the target string in the abnormal inverter at the target time, V 实时 is the voltage of the target string in the abnormal inverter at the target time, V 众数 is the voltage mode of the abnormal inverter at all times.

[0218] In an exemplary embodiment, the current mode can be obtained by using the Pearson mode method. For example, Mo = ξ-3 (ξ-M d );

[0219] Where: Mo refers to the mode value, ξ: refers to the sample mean, that is, the mean of the string current value, M d : The median of the sample values; where the sample mean is: Where (x i ): represents the current value of each string at that moment. At the same time, the values ​​with the mode of "negative numbers, 0, values ​​≤0.25A, and values ​​≥40A" are excluded.

[0220] Similarly, the voltage mode can also be obtained by the above-mentioned Pearson mode method.

[0221] In some embodiments, determining the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes:

[0222] Among them, ρ 日串流 is the daily current discrete rate of the target string in the abnormal inverter, f1 is the number of valid string current values, j represents the jth value of the valid string current value, x j日串流 is the current value collected at the jth moment, x 日串流 is the average value of the mode of current values ​​collected at all times; x 流众 is the mode of current at each moment;

[0223] Among them, ρ 日串压 is the daily voltage discrete rate of the target string in the abnormal inverter, f2 is the number of valid string voltage values, k represents the kth value of the valid string effective voltage value, x k日串压 is the voltage value collected at the kth moment, x 日串压 is the average value of the mode of voltage values ​​collected at all times; x 压众 is the voltage mode at each moment.

[0224] In an exemplary embodiment, the current discrete rate of each string in the abnormal inverter at each moment can be calculated by the above formula: The daily current discrete rate of each string in the abnormal inverter is obtained; based on the voltage discrete rate of each string in the abnormal inverter at each moment, through the above formula, The daily voltage dispersion rate of each string in the abnormal inverter is determined.

[0225] In some embodiments, the abnormal states of the multiple abnormal strings and the string fault types corresponding to the abnormal states include:

[0226] The first abnormal state of the abnormal string is that the current value is lower than the first threshold value within a predetermined time period, wherein the string fault type corresponding to the first abnormal state is a zero current string;

[0227] The second abnormal state of the abnormal string is that the hourly string current discrete rate monitored every day is a positive deviation, and the discrete rate is greater than 100%, or the hourly string voltage discrete rate every day is a positive deviation, and the discrete rate is greater than 100%, wherein the string fault type corresponding to the second abnormal state is an extremely large abnormal constant value string;

[0228] The third abnormal state of the abnormal string is that the similarity of the continuous periodic change of the hourly current discrete rate of the string reaches the second threshold, and when the string is blocked, the current discrete rate is negative, and after the shadow gradually disappears, the current discrete deviation rate gradually tends to normal; wherein, the string fault type corresponding to the third abnormal state is the shadow-blocked string;

[0229] The fourth abnormal state of the abnormal string is that the voltage discrete rate of the string changes suddenly from the normal discrete rate to the abnormal discrete rate; wherein the string fault type corresponding to the fourth abnormal state is a component damaged string;

[0230] The fifth abnormal state of the abnormal string is that if the voltage dispersion rate of the string is abnormal every hour of the day, the corresponding string current dispersion rate change is normal; wherein the string fault type corresponding to the fifth abnormal state is a terminal loose string;

[0231] The sixth abnormal state of the abnormal string is that the voltage and current discrete rates of the string change at the same frequency every day, and the linear regression method of the voltage and current discrete rates is adopted, and the trend shows a linear relationship; wherein the string fault type corresponding to the sixth abnormal state is a component mismatch string;

[0232] The seventh abnormal state of the abnormal string is that if the daily discrete rate of the string presents a linear change trend with an annual cycle, and the daily discrete rate increases daily; wherein, the string fault type corresponding to the seventh abnormal state is an attenuation abnormal string.

[0233] The present disclosure provides a computer-readable storage medium, on which a photovoltaic inverter string abnormality diagnosis and handling program based on discrete rate is stored. When the photovoltaic inverter string abnormality diagnosis and handling program based on discrete rate is executed by a processor, the photovoltaic inverter string abnormality diagnosis and handling method based on discrete rate described in the above embodiments is implemented.

[0234] The present disclosure provides a server, comprising a memory, a processor, and a discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program stored in the memory and executable on the processor. When the processor executes the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program, the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling method described in the above-mentioned embodiments is implemented.

[0235] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0236] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0237] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0238] In the present disclosure, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0239] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A method for diagnosing and handling abnormalities of photovoltaic inverter strings based on discrete rate. It is characterized in that include: Obtain the current discrete rate and voltage discrete rate of each inverter at each moment; Determine the daily discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment; Based on the daily discrete rate of each inverter, an abnormal inverter among the inverters is determined; Obtaining the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; Determine the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; Determining the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or the daily voltage discrete rate of each string in the abnormal inverter; Based on the abnormal string root cause diagnosis model, the abnormal strings in the abnormal inverter are diagnosed to determine the string fault type of the abnormal strings, and based on the string fault type of the abnormal strings, a disposal plan corresponding to the string fault type of the abnormal strings is determined; wherein the abnormal string root cause diagnosis model includes a plurality of abnormal states of abnormal strings and the string fault types corresponding to the abnormal states.

2. The photovoltaic inverter string abnormality diagnosis and treatment method based on discrete rate according to claim 1, It is characterized in that The obtaining of the current discrete rate and the voltage discrete rate of each inverter at each moment includes: Get the current discrete rate ρ of a single inverter at each moment 流 : Among them, n is the number of valid strings, i represents the i-th string, x i is the effective current value of the effective string at the i-th moment, and x is the current mode value of the current values ​​collected by all strings at all times; Get the voltage discrete rate ρ of a single inverter at each moment 压 : Where n is the number of valid strings, i represents the i-th string, y i is the effective voltage value of the effective string at the i-th moment, and y is the voltage mode value of the voltage values ​​collected by all strings at all times.

3. The method for diagnosing and handling abnormality of photovoltaic inverter strings based on discrete rate according to claim 1, It is characterized in that The determining the daily discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment includes: Determine the comprehensive discrete rate of each inverter based on the current discrete rate and voltage discrete rate of each inverter at each moment; Based on the comprehensive discrete rate of each inverter, the daily discrete rate of each inverter is determined.

4. The method for diagnosing and handling abnormality of photovoltaic inverter strings based on discrete rate according to claim 1, It is characterized in that The step of determining the daily discrete rate of each inverter based on the comprehensive discrete rate of each inverter includes: ρ i is the comprehensive discrete rate of a single inverter at each i-th moment, ρ 日 is the daily discrete rate of a single inverter, and m is the number of measurements at all times within the effective time range of a single inverter.

5. The photovoltaic inverter string abnormality diagnosis and treatment method based on discrete rate according to claim 1, It is characterized in that The obtaining of the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes: ρ 串流 =(I 实时 -I 众数 ) / I 众数 *100%; where ρ 串流 is the current discrete rate of the target string in the abnormal inverter at the target time, I 实时 is the current of the target string in the abnormal inverter at the target time, I 众数 is the mode of current of the abnormal inverter at all times; ρ 串压 =(V 实时 -V 众数 ) / V 众数 *100%; where ρ 串压 is the voltage discrete rate of the target string in the abnormal inverter at the target time, V 实时 is the voltage of the target string in the abnormal inverter at the target time, V 众数 is the voltage mode of the abnormal inverter at all times.

6. The method for diagnosing and handling abnormality of photovoltaic inverter strings based on discrete rate according to claim 1, It is characterized in that The determining of the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment includes: Among them, ρ 日串流 is the daily current discrete rate of the target string in the abnormal inverter, f1 is the number of valid string current values, j represents the jth value of the valid string current value, x j日串流 is the current value collected at the jth moment, x 日串流 is the average value of the mode of current values ​​collected at all times; x 流众 is the mode of current at each moment; Among them, ρ 日串压 is the daily voltage discrete rate of the target string in the abnormal inverter, f2 is the number of valid string voltage values, k represents the kth value of the valid string effective voltage value, x k日串压 is the voltage value collected at the kth moment, x 日串压 is the average value of the mode of voltage values ​​collected at all times; x 压众 is the voltage mode at each moment.

7. The photovoltaic inverter string abnormality diagnosis and treatment method based on discrete rate according to claim 1, It is characterized in that The abnormal states of the various abnormal strings and the string fault types corresponding to the abnormal states include: The first abnormal state of the abnormal string is that the current value is lower than the first threshold value within a predetermined time period, wherein the string fault type corresponding to the first abnormal state is a zero current string; The second abnormal state of the abnormal string is that the hourly string current discrete rate monitored every day is a positive deviation, and the discrete rate is greater than 100%, or the hourly string voltage discrete rate every day is a positive deviation, and the discrete rate is greater than 100%, wherein the string fault type corresponding to the second abnormal state is an extremely large abnormal constant value string; The third abnormal state of the abnormal string is that the similarity of the continuous periodic change of the hourly current discrete rate of the string reaches the second threshold, and when the string is blocked, the current discrete rate is negative, and after the shadow gradually disappears, the current discrete deviation rate gradually tends to normal; wherein, the string fault type corresponding to the third abnormal state is the shadow-blocked string; The fourth abnormal state of the abnormal string is that the voltage discrete rate of the string changes suddenly from the normal discrete rate to the abnormal discrete rate; wherein the string fault type corresponding to the fourth abnormal state is a component damaged string; The fifth abnormal state of the abnormal string is that if the voltage dispersion rate of the string is abnormal every hour of the day, the corresponding string current dispersion rate change is normal; wherein the string fault type corresponding to the fifth abnormal state is a terminal loose string; The sixth abnormal state of the abnormal string is that the voltage and current discrete rates of the string change at the same frequency every day, and the linear regression method of the voltage and current discrete rates is adopted, and the trend shows a linear relationship; wherein the string fault type corresponding to the sixth abnormal state is a component mismatch string; The seventh abnormal state of the abnormal string is that if the daily discrete rate of the string presents a linear change trend with an annual cycle, and the daily discrete rate increases daily; wherein, the string fault type corresponding to the seventh abnormal state is an attenuation abnormal string.

8. A photovoltaic inverter string abnormality diagnosis and treatment device based on discrete rate, It is characterized in that include: A first discrete rate acquisition module is used to acquire the current discrete rate and voltage discrete rate of each inverter at each moment; A first daily discrete rate determination module, configured to determine the daily discrete rate of each inverter based on the current discrete rate and the voltage discrete rate of each inverter at each moment; An abnormal inverter determination module, used for determining an abnormal inverter among the inverters based on the daily discrete rate of each inverter; A second discrete rate acquisition module is used to acquire the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; A second daily discrete rate determination module is used to determine the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter based on the current discrete rate and / or voltage discrete rate of each string in the abnormal inverter at each moment; An abnormal string determination module is used to determine the abnormal strings in the abnormal inverter based on the daily current discrete rate and / or daily voltage discrete rate of each string in the abnormal inverter; A string fault diagnosis module is used to diagnose the abnormal strings in the abnormal inverter based on an abnormal string root cause diagnosis model, determine the string fault type of the abnormal strings, and determine a treatment plan corresponding to the string fault type of the abnormal strings based on the string fault type of the abnormal strings; wherein the abnormal string root cause diagnosis model includes a plurality of abnormal states of abnormal strings and the string fault types corresponding to the abnormal states.

9. A computer-readable storage medium, It is characterized in that A discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program is stored thereon. When the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program is executed by a processor, the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling method described in any one of claims 1 to 7 is implemented.

10. A server, It is characterized in that The invention comprises a memory, a processor and a discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program stored in the memory and executable on the processor. When the processor executes the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling program, the discrete rate-based photovoltaic inverter string abnormality diagnosis and handling method described in any one of claims 1 to 7 is implemented.

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