A photovoltaic inverter fault prediction method

Abstract

The present invention relates to the field of photovoltaic inverter fault detection technology, and discloses a photovoltaic inverter fault prediction method, wherein a data collection module is composed of a current monitoring unit, a voltage monitoring unit, and a temperature monitoring unit. The photovoltaic inverter fault prediction method continuously collects relevant data values ​​of the photovoltaic inverter through the data collection module, and a threshold corresponding to the fluctuation value is preset in the data analysis module, and the fluctuation value is compared with the corresponding threshold value respectively. When the fluctuation value exceeds the value range of the corresponding threshold value, it is determined that the fluctuation value is abnormal, and a corresponding fault signal is issued. When the fault feedback module receives the fault signal or the abnormal signal, it issues a corresponding fault signal and fault information. When the operation and maintenance personnel observe the fault signal and the fault information, they can timely repair and maintain the fault of the photovoltaic inverter according to the fault information, so as to avoid the photovoltaic inverter from continuing to work with the fault, resulting in irreversible damage to the photovoltaic inverter.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic inverter fault detection, and in particular to a photovoltaic inverter fault prediction method. Background Art

[0002] A photovoltaic inverter is an electronic device used to convert the direct current (DC) electricity generated by solar photovoltaic panels (also known as photovoltaic panels) into alternating current (AC) electricity. A photovoltaic inverter is a key component in a photovoltaic power generation system. Its function is to convert the direct current generated by solar panels into alternating current that can be used by the power grid. The photovoltaic inverter controls and converts the direct current through electronic components and circuits. Based on the characteristics of the direct current generated by the photovoltaic panels, it converts it into alternating current that meets the requirements of the power grid, so that its frequency, voltage and waveform match those of the power grid, thereby transmitting the electricity generated by the photovoltaic power generation system to the power grid.

[0003] However, at present, most of the time, the photovoltaic inverter is only detected when it fails. The fault of the photovoltaic inverter is detected to determine what kind of fault the photovoltaic inverter has. This detection method cannot monitor the operating status of the inverter in real time, resulting in the operation and maintenance personnel being unable to promptly discover the fault of the photovoltaic inverter when the photovoltaic inverter just fails, so that the photovoltaic inverter continues to operate with the fault, causing irreversible damage to the photovoltaic inverter. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the deficiencies in the prior art, the present invention provides a photovoltaic inverter fault prediction method, which has the characteristics of continuously collecting relevant data values ​​of the photovoltaic inverter through a data collection module, sending the collected relevant data values ​​to a data processing module, and the data processing module respectively calculates the fluctuation values ​​of the corresponding values. The data processing module sends the calculated fluctuation values ​​of the corresponding values ​​to a data analysis module, and the data analysis module is preset with thresholds corresponding to the fluctuation values, and the fluctuation values ​​are compared with the corresponding thresholds respectively. When the fluctuation value exceeds the value range of the corresponding threshold, it is determined that the fluctuation value is abnormal, and a corresponding fault signal or abnormal signal is sent. When the fault occurs, When the fault feedback module receives a fault signal or an abnormal signal, it sends out a corresponding fault signal and fault information. When the operation and maintenance personnel observe the fault signal and fault information, they can promptly repair and maintain the fault of the photovoltaic inverter according to the fault information to avoid the photovoltaic inverter from continuing to work with the fault, resulting in irreversible damage to the photovoltaic inverter. At the same time, the operation and maintenance personnel can carry the corresponding maintenance tools to repair and maintain the photovoltaic inverter according to the fault signal and fault information, which improves the efficiency of photovoltaic inverter maintenance, reduces the number of tools carried by the operation and maintenance personnel, reduces the burden on the operation and maintenance personnel, and solves the above-mentioned problems.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solution: a photovoltaic inverter fault prediction method, comprising the following steps:

[0008] S1, the data collection module continuously collects relevant data values ​​of the photovoltaic inverter, and sends the collected data to the data processing module through the network;

[0009] S2, the data processing module analyzes and calculates the data values ​​according to the corresponding mathematical model, and sends the calculated change values ​​to the data analysis module through the network;

[0010] S3, the data analysis module compares the various change values ​​with the corresponding change value thresholds preset internally, analyzes the data, and when abnormal data appears, the data analysis module sends a fault signal to the fault feedback module through the network;

[0011] S4. After receiving the fault signal, the fault feedback module issues a fault alarm and displays specific fault information.

[0012] Preferably, the data collection module is composed of a current monitoring unit, a voltage monitoring unit and a temperature monitoring unit. The current monitoring unit is used to obtain the real-time current value D1 of the photovoltaic inverter during operation, the voltage monitoring unit is used to obtain the real-time voltage value Dy of the photovoltaic inverter during operation, and the temperature monitoring unit is used to obtain the real-time temperature value Wd of the photovoltaic inverter during operation. The data collection module sends the acquired real-time current value D1, real-time voltage value Dy and real-time temperature value Wd to the data processing module through the network, and the data processing module calculates the corresponding fluctuation values ​​for these data respectively.

[0013] Preferably, the current fluctuation value algorithm formula is as follows:

[0014]

[0015] In the formula, Dlbd represents the current fluctuation value, Dl is the reciprocal of the number of collected data points, 10, where 10 represents 10 data points. n+9 Indicates the real-time current value of the 10th data point, Dl n+9 +Dl n+8 +...+Dl n / 10 means the average value of the real-time current values ​​of 10 data points.

[0016] 5. Preferably, the voltage fluctuation value algorithm formula is as follows:

[0017]

[0018] In the formula, Dybd represents the voltage fluctuation value, It represents the reciprocal of 10, the number of collected data points, where 10 means 10 data points are grouped together. Indicates the average value of 10 real-time voltage values, Dy n+9 Indicates the 10th collected real-time voltage value.

[0019] Preferably, the temperature fluctuation value algorithm formula is as follows:

[0020]

[0021] In the formula, Wdbd represents the real-time temperature fluctuation value. It represents the reciprocal of the number of collected data points, 5, where 5 is a group of 5 data points. Indicates the average value of 5 real-time temperature values, Wd n+4 Indicates the fifth real-time temperature value collected.

[0022] Preferably, the data processing module sends the calculated current fluctuation value, voltage fluctuation value or temperature fluctuation value to the data analysis module through a network.

[0023] Preferably, a current fluctuation threshold Dlyz is preset in the data analysis module, and the data analysis module compares the calculated current fluctuation value with the current fluctuation threshold Dlyz. When the current fluctuation value exceeds the value range of the current fluctuation threshold Dlyz, it is determined to be a current abnormality, and a photovoltaic inverter current fault signal is sent to the fault feedback module.

[0024] Preferably, a voltage fluctuation threshold Dyyz is preset in the data analysis module. The data analysis module compares the calculated voltage fluctuation value with the voltage fluctuation threshold Dyyz. When the voltage fluctuation value exceeds the value range of the voltage fluctuation threshold Dyyz, it is determined to be a voltage abnormality and a photovoltaic inverter voltage fault signal is sent to the fault feedback module.

[0025] Preferably, a temperature fluctuation threshold Wdyz is preset in the data analysis module. The data analysis module compares the calculated temperature fluctuation value with the temperature fluctuation threshold Wdyz. When the temperature fluctuation value exceeds the value range of the temperature fluctuation threshold Wdyz, it is determined to be a temperature abnormality, and a photovoltaic inverter temperature abnormality signal is sent to the fault feedback module.

[0026] Preferably, the fault feedback module is provided with a display screen for displaying abnormal signals;

[0027] When the fault feedback module receives a photovoltaic inverter current fault signal, the fault module displays that the photovoltaic inverter current is abnormal;

[0028] When the fault feedback module receives a photovoltaic inverter voltage fault signal, the fault module displays that the photovoltaic inverter voltage is abnormal;

[0029] When the fault feedback module receives a photovoltaic inverter temperature abnormality signal, the fault module displays that the photovoltaic inverter temperature is abnormal.

[0030] Compared with the prior art, the present invention provides a photovoltaic inverter fault prediction method, which has the following beneficial effects:

[0031] The present invention continuously collects relevant data values ​​of the photovoltaic inverter through a data collection module, and sends the collected relevant data values ​​to a data processing module. The data processing module calculates fluctuation values ​​of corresponding values ​​respectively, and the data processing module sends the calculated fluctuation values ​​of corresponding values ​​to a data analysis module. The data analysis module is preset with thresholds of corresponding fluctuation values, and the fluctuation values ​​are compared with corresponding thresholds respectively. When the fluctuation value exceeds the value range of the corresponding threshold, it is determined that the fluctuation value is abnormal, and a corresponding fault signal or abnormal signal is sent. When the fault feedback module receives the fault signal or abnormal signal, a corresponding fault signal and fault information are sent. When the operation and maintenance personnel observe the fault signal and the fault information, they can timely repair and maintain the fault of the photovoltaic inverter according to the fault information, so as to avoid the photovoltaic inverter from continuing to work with the fault, resulting in irreversible damage to the photovoltaic inverter. At the same time, the operation and maintenance personnel can carry corresponding maintenance tools to repair and maintain the photovoltaic inverter according to the fault signal and the fault information, thereby improving the efficiency of photovoltaic inverter maintenance, and can also reduce the number of tools carried by the operation and maintenance personnel, thereby reducing the burden on the operation and maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the steps of the method of the present invention;

[0033] Figure 2 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] At present, most of the time, the photovoltaic inverter is detected only when it fails. The fault of the photovoltaic inverter is detected to find out what kind of fault the photovoltaic inverter has. This detection method cannot monitor the operating status of the inverter in real time, resulting in the operation and maintenance personnel being unable to discover the fault of the photovoltaic inverter in time when the photovoltaic inverter just fails, causing the photovoltaic inverter to continue to operate with the fault, causing irreversible damage to the photovoltaic inverter. Therefore, a photovoltaic inverter fault prediction method is proposed. Please refer to Figure 1 The specific steps of this method are as follows:

[0036] S1, the data collection module continuously collects relevant data values ​​of the photovoltaic inverter, and sends the collected data to the data processing module through the network;

[0037] S2, the data processing module analyzes and calculates the data values ​​according to the corresponding mathematical model, and sends the calculated change values ​​to the data analysis module through the network;

[0038] S3, the data analysis module compares the various change values ​​with the corresponding change value thresholds preset internally, analyzes the data, and when abnormal data appears, the data analysis module sends a fault signal to the fault feedback module through the network;

[0039] S4. After receiving the fault signal, the fault feedback module issues a fault alarm and displays specific fault information.

[0040] See also Figure 2 The data collection module in the above method is composed of a current monitoring unit, a voltage monitoring unit and a temperature monitoring unit, wherein:

[0041] The current monitoring unit is used to obtain the real-time current value D1 of the photovoltaic inverter during operation;

[0042] The voltage monitoring unit is used to obtain the real-time voltage value Dy of the photovoltaic inverter during operation;

[0043] The temperature monitoring unit is used to obtain the real-time temperature value Wd of the photovoltaic inverter during operation;

[0044] The data collection module sends the acquired real-time current value D1, real-time voltage value Dy and real-time temperature value Wd to the data processing module through the network;

[0045] The data processing module calculates the corresponding fluctuation values ​​for these data respectively. The specific algorithm formulas for multiple fluctuation values ​​are as follows:

[0046] The current fluctuation value algorithm formula is as follows:

[0047]

[0048] In the formula, Dlbd represents the current fluctuation value, Dl is the reciprocal of the number of collected data points, 10, where 10 represents 10 data points. n+9 Indicates the real-time current value of the 10th data point, Dl n+9 +Dl n+8 +...+Dl n / 10 means the average value of the real-time current value of 10 data points;

[0049] The voltage fluctuation value algorithm formula is as follows:

[0050]

[0051] In the formula, Dybd represents the voltage fluctuation value, It represents the reciprocal of 10, the number of collected data points, where 10 means 10 data points are grouped together. Indicates the average value of 10 real-time voltage values, Dy n+9 Indicates the 10th collected real-time voltage value;

[0052] The temperature fluctuation value algorithm formula is as follows:

[0053]

[0054] In the formula, Wdbd represents the real-time temperature fluctuation value. It represents the reciprocal of the number of collected data points, 5, where 5 is a group of 5 data points. Indicates the average value of 5 real-time temperature values, Wd n+4 Indicates the fifth real-time temperature value collected;

[0055] The data processing module sends the calculated current fluctuation value, voltage fluctuation value or temperature fluctuation value to the data analysis module through the network, and the data analysis module is respectively preset with a current fluctuation threshold Dlyz, a voltage fluctuation threshold Dyyz and a temperature fluctuation threshold Wdyz;

[0056] The data analysis module compares the calculated current fluctuation value with the current fluctuation threshold Dlyz. When the current fluctuation value exceeds the value range of the current fluctuation threshold Dlyz, it is determined to be a current abnormality and a photovoltaic inverter current fault signal is sent to the fault feedback module.

[0057] The data analysis module compares the calculated voltage fluctuation value with the voltage fluctuation threshold Dyyz. When the voltage fluctuation value exceeds the value range of the voltage fluctuation threshold Dyyz, it is determined to be a voltage abnormality and a photovoltaic inverter voltage fault signal is sent to the fault feedback module.

[0058] The data analysis module compares the calculated temperature fluctuation value with the temperature fluctuation threshold Wdyz. When the temperature fluctuation value exceeds the value range of the temperature fluctuation threshold Wdyz, it is determined to be a temperature abnormality and a photovoltaic inverter temperature abnormality signal is sent to the fault feedback module.

[0059] When the fault feedback module receives the photovoltaic inverter current fault signal, the fault module displays that the photovoltaic inverter current is abnormal;

[0060] When the fault feedback module receives a photovoltaic inverter voltage fault signal, the fault module displays that the photovoltaic inverter voltage is abnormal;

[0061] When the fault feedback module receives a signal indicating abnormal temperature of the photovoltaic inverter, the fault module displays that the temperature of the photovoltaic inverter is abnormal;

[0062] The fault module also includes a display for displaying abnormal signals. When a fault occurs in the photovoltaic inverter, the display displays the fault signal and fault information corresponding to the photovoltaic inverter. Then, the operation and maintenance personnel can make timely responses based on the displayed fault signal and fault information.

[0063] The data collection module continuously collects the relevant data values ​​of the photovoltaic inverter, and sends the collected relevant data values ​​to the data processing module. The data processing module calculates the fluctuation values ​​of the corresponding values ​​respectively, and the data processing module sends the calculated fluctuation values ​​of the corresponding values ​​to the data analysis module. The data analysis module is preset with thresholds of corresponding fluctuation values, and the fluctuation values ​​are compared with the corresponding thresholds respectively. When the fluctuation value exceeds the value range of the corresponding threshold, it is determined that the fluctuation value is abnormal, and a corresponding fault signal or abnormal signal is issued. When the fault feedback module receives the fault signal or abnormal signal, it issues a corresponding fault signal and fault information. When the operation and maintenance personnel observe the fault signal and fault information, they can timely repair and maintain the fault of the photovoltaic inverter according to the fault information, so as to avoid the photovoltaic inverter from continuing to work with the fault, resulting in irreversible damage to the photovoltaic inverter. At the same time, the operation and maintenance personnel can carry the corresponding maintenance tools to repair and maintain the photovoltaic inverter according to the fault signal and fault information, which improves the efficiency of photovoltaic inverter maintenance, and can also reduce the number of tools carried by the operation and maintenance personnel, and reduce the burden on the operation and maintenance personnel.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A photovoltaic inverter fault prediction method, characterized in that: The following steps are involved: S1. The data collection module continuously collects relevant data values ​​of the photovoltaic inverter, and sends the collected data to the data processing module through the network. The data collection module is composed of a current monitoring unit, a voltage monitoring unit and a temperature monitoring unit. The current monitoring unit is used to obtain the real-time current value D1 of the photovoltaic inverter during operation, the voltage monitoring unit is used to obtain the real-time voltage value Dy of the photovoltaic inverter during operation, and the temperature monitoring unit is used to obtain the real-time temperature value Wd of the photovoltaic inverter during operation. The data collection module sends the obtained real-time current value D1, real-time voltage value Dy and real-time temperature value Wd to the data processing module through the network, and the data processing module calculates the corresponding fluctuation values ​​for these data respectively; The current fluctuation value algorithm formula is as follows: In the formula, Dlbd represents the current fluctuation value, Dl is the reciprocal of the number of collected data points, 10, where 10 represents 10 data points. n+9 Indicates the real-time current value of the 10th data point, Dl n+9 +Dl n+8 +...+Dl n / 10 means the average value of the real-time current value of 10 data points; The voltage fluctuation value algorithm formula is as follows: In the formula, Dybd represents the voltage fluctuation value, It represents the reciprocal of 10, the number of collected data points, where 10 means 10 data points are grouped together. Indicates the average value of 10 real-time voltage values, Dy n+9 Indicates the 10th collected real-time voltage value; The temperature fluctuation value algorithm formula is as follows: In the formula, Wdbd represents the real-time temperature fluctuation value. It represents the reciprocal of the number of collected data points, 5, where 5 is a group of 5 data points. Indicates the average value of 5 real-time temperature values, Wd n+4 Indicates the fifth real-time temperature value collected; The data processing module sends the calculated current fluctuation value, voltage fluctuation value or temperature fluctuation value to the data analysis module through the network; S2, the data processing module analyzes and calculates the data values ​​according to the corresponding mathematical model, and sends the calculated change values ​​to the data analysis module through the network; S3, the data analysis module compares the various change values ​​with the corresponding change value thresholds preset internally, analyzes the data, and when abnormal data appears, the data analysis module sends a fault signal to the fault feedback module through the network; S4. After receiving the fault signal, the fault feedback module issues a fault alarm and displays specific fault information.

2. A photovoltaic inverter fault prediction method according to claim 1, characterized in that: The data processing module sends the calculated current fluctuation value, voltage fluctuation value or temperature fluctuation value to the data analysis module through the network.

3. A photovoltaic inverter fault prediction method according to claim 2, characterized in that: A current fluctuation threshold Dlyz is preset in the data analysis module. The data analysis module compares the calculated current fluctuation value with the current fluctuation threshold Dlyz. When the current fluctuation value exceeds the value range of the current fluctuation threshold Dlyz, it is determined to be a current abnormality and a photovoltaic inverter current fault signal is sent to the fault feedback module.

4. A photovoltaic inverter fault prediction method according to claim 3, characterized in that: A voltage fluctuation threshold Dyyz is preset in the data analysis module. The data analysis module compares the calculated voltage fluctuation value with the voltage fluctuation threshold Dyyz. When the voltage fluctuation value exceeds the value range of the voltage fluctuation threshold Dyyz, it is determined to be a voltage abnormality and a photovoltaic inverter voltage fault signal is sent to the fault feedback module.

5. A photovoltaic inverter fault prediction method according to claim 4, characterized in that: A temperature fluctuation threshold Wdyz is preset in the data analysis module. The data analysis module compares the calculated temperature fluctuation value with the temperature fluctuation threshold Wdyz. When the temperature fluctuation value exceeds the value range of the temperature fluctuation threshold Wdyz, it is determined to be a temperature abnormality and a photovoltaic inverter temperature abnormality signal is sent to the fault feedback module.

6. A photovoltaic inverter fault prediction method according to claim 5, characterized in that: The fault feedback module is provided with a display screen for displaying abnormal signals; When the fault feedback module receives a photovoltaic inverter current fault signal, the fault module displays that the photovoltaic inverter current is abnormal; When the fault feedback module receives a photovoltaic inverter voltage fault signal, the fault module displays that the photovoltaic inverter voltage is abnormal; When the fault feedback module receives a photovoltaic inverter temperature abnormality signal, the fault module displays that the photovoltaic inverter temperature is abnormal.

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