Intelligent operation and maintenance supervision control system for distributed photovoltaic power generation equipment

Abstract

The invention belongs to the technical field of power generation equipment supervision, and particularly relates to a distributed photovoltaic power generation equipment intelligent operation and maintenance supervision control system which comprises a power generation equipment stability detection module, a power anomaly analysis module, an illumination tracking analysis module, an operation and maintenance early warning control module and a remote supervision end. According to the invention, the stability condition of the photovoltaic power generation equipment is detected and analyzed through the power generation equipment stability detection module, and the power generation abnormity of the photovoltaic power generation equipment is analyzed through the power abnormity analysis module when a stability qualified signal is generated. When a power generation safety signal is generated, the light tracking analysis module analyzes the light tracking operation performance of the photovoltaic power generation equipment, and can carry out step-by-step progressive accurate analysis and timely early warning on the stability condition, the electric power risk and the light tracking performance of the photovoltaic power generation equipment, thereby achieving the targeted monitoring of the photovoltaic power generation equipment. And safe, stable and efficient operation of photovoltaic power generation equipment can be ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation equipment supervision, and in particular to an intelligent operation and maintenance supervision and control system for distributed photovoltaic power generation equipment. Background Art

[0002] Photovoltaic power generation equipment is related equipment that uses the photovoltaic effect of solar energy to generate electricity. Photovoltaic power generation is based on the principle of photovoltaic effect to directly convert light energy into electrical energy. With the continuous advancement of technology and the reduction of costs, photovoltaic power generation plays an increasingly important role in the energy field.

[0003] A photovoltaic equipment operation and maintenance system is disclosed in a Chinese invention patent with publication number CN117614110A. The photovoltaic equipment operation and maintenance system includes an operation and maintenance platform and multiple monitoring robots, which can improve the accuracy and efficiency of operation and maintenance and avoid damage to photovoltaic equipment.

[0004] However, in actual application, the above-mentioned technical solution of the invention cannot conduct a step-by-step and accurate analysis of the stability, power risk and light tracking performance of photovoltaic power generation equipment and provide timely warnings, making it difficult to achieve targeted monitoring of photovoltaic power generation equipment and reasonable operation and maintenance control, which is not conducive to ensuring the safe, stable and efficient operation of photovoltaic power generation equipment.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0006] The purpose of the present invention is to provide an intelligent operation and maintenance supervision and control system for distributed photovoltaic power generation equipment, which solves the problem that the prior art is unable to conduct gradual and progressive accurate analysis and timely warning of the stability status, power risk and light tracking performance of photovoltaic power generation equipment, and it is difficult to achieve targeted monitoring and reasonable operation and maintenance control of photovoltaic power generation equipment, which is not conducive to ensuring the safe, stable and efficient operation of photovoltaic power generation equipment.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system, including a power generation equipment stability detection module, a power anomaly analysis module, a light tracking analysis module, an operation and maintenance early warning control module and a remote supervision terminal;

[0009] The power generation equipment stability detection module detects and analyzes the stability status of the photovoltaic power generation equipment, generates a stability hidden danger signal or a stability qualified signal based on the stability hidden danger signal, sends the stability hidden danger signal to the operation and maintenance early warning control module, and sends the stability qualified signal to the power anomaly analysis module;

[0010] When the power anomaly analysis module receives the stable qualified signal, it analyzes the power generation anomaly of the photovoltaic power generation equipment, generates a power generation warning signal or a power generation safety signal accordingly, and sends the power generation warning signal to the operation and maintenance warning control module, and sends the power generation safety signal to the light tracking analysis module;

[0011] The photovoltaic power generation equipment automatically adjusts its tilt angle based on the direction of light. When the light tracking analysis module receives the power generation safety signal, it analyzes the light tracking operation performance of the photovoltaic power generation equipment per unit time, generates a light tracking qualified signal or a light tracking abnormal signal through analysis, and sends the light tracking abnormal signal to the operation and maintenance early warning control module;

[0012] The operation and maintenance warning control module generates corresponding warning information when receiving a stability hidden danger signal, a power generation warning signal or a light tracking abnormality signal, and sends the generated warning information to the remote monitoring terminal for display.

[0013] Furthermore, the specific analysis process of the photovoltaic equipment stability detection module includes:

[0014] The shaking frequency and shaking amplitude of the photovoltaic power generation equipment are collected, and the shaking frequency and shaking amplitude are numerically compared with the preset shaking frequency threshold and the preset shaking amplitude threshold respectively. If the shaking frequency or shaking amplitude exceeds the corresponding preset threshold, it is judged that the photovoltaic power generation equipment is in an unstable state;

[0015] Obtain all single durations of the photovoltaic power generation equipment being in an unstable state within a unit time, sum up all single durations of the photovoltaic power generation equipment being in an unstable state within a unit time to obtain a total unstable time value, and mark the number of single durations exceeding the corresponding preset single duration threshold within a unit time as an unstable dangerous frequency value;

[0016] The total unstable time value and the unstable dangerous frequency value are numerically compared with the preset total unstable time threshold and the unstable dangerous frequency threshold, respectively. If the total unstable time value or the unstable dangerous frequency value exceeds the corresponding preset threshold, a stable hidden danger signal is generated;

[0017] If the total unstable time value and the unstable risk frequency value do not exceed the corresponding preset thresholds, the support hidden danger coefficient is obtained through support hidden danger assessment analysis, and the support hidden danger coefficient is numerically compared with the preset support hidden danger coefficient threshold. If the support hidden danger coefficient exceeds the preset support hidden danger coefficient threshold, a stable hidden danger signal is generated; if the support hidden danger coefficient does not exceed the preset support hidden danger coefficient threshold, a stable qualified signal is generated.

[0018] Furthermore, the specific analysis process supporting the hidden danger assessment and analysis is as follows:

[0019] The supporting structure of the photovoltaic power generation equipment is monitored, the sinking amount of the supporting structure compared with the initial time is collected and marked as the support sinking table value, and a number of detection points are set on the supporting structure, the real-time distance value between the corresponding two groups of detection points is collected and the deviation value from the corresponding initial distance value is marked as the point spacing deformation value, the point spacing deformation value is numerically compared with the corresponding preset point spacing deformation threshold, if the point spacing deformation value exceeds the preset point spacing deformation threshold, the corresponding point spacing deformation value is marked as the point spacing abnormality value, the number of point spacing abnormality values ​​is obtained and the ratio of the value to the number of point spacing deformation values ​​is calculated to obtain the point spacing abnormality value;

[0020] The ratio of the point spacing deformation value to the corresponding preset point spacing deformation threshold is marked as the point spacing deformation share value, the point spacing deformation value is obtained by averaging all the point spacing deformation values, and the support hidden danger coefficient is obtained by numerically calculating the support settlement value, the point spacing deformation risk value and the point spacing deformation value.

[0021] Furthermore, the specific analysis process of the power anomaly analysis module is as follows:

[0022] The voltage curve and current curve of the photovoltaic power generation equipment per unit time are obtained, and the voltage curve and the current curve are placed in the first quadrant of the corresponding rectangular coordinate system respectively, and all turning points on the voltage curve are obtained. The ratio of the Y-direction distance value between two adjacent groups of turning points to the corresponding X-direction distance value is marked as the pressure change coefficient, and the rheological coefficient is obtained in the same way;

[0023] The number of pressure variation coefficients exceeding the preset pressure variation coefficient threshold value per unit time is obtained and marked as the pressure variation test value, and the number of flow coefficients exceeding the preset flow coefficient threshold value per unit time is marked as the flow variation test value; and the Y-direction distance value between the highest point and the lowest point on the voltage curve per unit time is marked as the pressure amplitude measurement value, and the flow amplitude measurement value is obtained similarly;

[0024] The power abnormality evaluation value is obtained by numerically calculating the pressure variation detection value, flow variation detection value, pressure amplitude measurement value and flow amplitude measurement value, and the power abnormality evaluation value is numerically compared with the preset power abnormality evaluation threshold value. If the power abnormality evaluation value exceeds the preset power abnormality evaluation threshold value, a power generation warning signal is generated.

[0025] Furthermore, if the power abnormality evaluation value does not exceed the preset power abnormality evaluation threshold, the deviation value of the real-time grounding resistance value of the photovoltaic power generation equipment compared with the preset standard grounding resistance value is marked as the grounding resistance deviation value, and the deviation value of the real-time insulation resistance value of the photovoltaic power generation equipment compared with the preset standard insulation resistance value is marked as the insulation resistance deviation value, and the average of all grounding resistance deviation values ​​within a unit time is calculated to obtain the grounding resistance table value, and the average of all insulation resistance deviation values ​​within a unit time is calculated to obtain the insulation resistance table value;

[0026] The actual power generation and electric energy output value of the photovoltaic power generation equipment per unit time are collected, and the ratio of the electric energy output value to the actual power generation is marked as the power generation output meter value. The power alarm value is obtained by numerically calculating the power abnormality value, the grounding resistance meter value, the insulation resistance meter value and the power generation output meter value. The power alarm value is numerically compared with the preset power alarm threshold. If the power alarm value exceeds the preset power alarm threshold, a power generation early warning signal is generated; if the power alarm value does not exceed the preset power alarm threshold, a power generation safety signal is generated.

[0027] Furthermore, the specific analysis process of the light tracing analysis module includes:

[0028] The actual tilt angle of the photovoltaic power generation equipment is collected, and the deviation value between the actual tilt angle and the corresponding preset standard tilt angle is marked as a tilt detection value, and the tilt detection value is numerically compared with a preset tilt detection threshold. If the tilt detection value exceeds the preset tilt detection threshold, the corresponding tilt detection value is marked as a tilt deviation value;

[0029] The number of inclination deviation values ​​per unit time is obtained and the ratio thereof is calculated with the number of inclination detection values ​​to obtain the inclination abnormality value, and the average of all inclination detection values ​​per unit time is calculated to obtain the inclination detection value; the inclination abnormality value and the inclination analysis value are numerically compared with the preset inclination abnormality threshold and the preset inclination analysis threshold respectively; if the inclination abnormality value or the inclination analysis value exceeds the corresponding preset threshold, a light tracking abnormality signal is generated.

[0030] Furthermore, if the tilt angle abnormality value and the tilt angle detection value do not exceed the corresponding preset threshold value, when the photovoltaic power generation equipment adjusts the tilt angle, the average value and variance value of the adjustment speed of the corresponding adjustment process are collected and marked as the adjustment speed value and the adjustment speed wave value, respectively, and the average value of the noise decibel value generated in the corresponding adjustment process is marked as the adjustment noise value, and the deviation value of the adjustment speed value from the corresponding preset standard adjustment speed value is marked as the adjustment speed abnormality value;

[0031] The adjustment table evaluation value is obtained by numerically calculating the adjustment speed difference value, the adjustment speed wave value and the adjustment noise condition value, and the adjustment table evaluation value is numerically compared with the preset adjustment table evaluation threshold value. If the adjustment table evaluation value exceeds the preset adjustment table evaluation threshold value, the corresponding adjustment process is marked as an adjustment difference process;

[0032] The number of anomaly processes per unit time is obtained and the ratio is calculated with the total number of adjustment processes to obtain the anomaly detection value, and the adjustment table evaluation values ​​of all adjustment processes per unit time are averaged to obtain the adjustment analysis value, and the anomaly detection value and the adjustment analysis value are numerically compared with the preset anomaly detection threshold and the preset adjustment analysis threshold respectively. If the anomaly detection value or the adjustment analysis value exceeds the corresponding preset threshold, an illumination tracking abnormality signal is generated; if both the anomaly detection value and the adjustment analysis value do not exceed the corresponding preset threshold, a illumination tracking qualified signal is generated.

[0033] Furthermore, the operation and maintenance warning control module is communicatively connected to the replacement evaluation decision module, and the operation and maintenance warning control module sends the generated warning information to the replacement evaluation decision module. When the replacement evaluation decision module receives the corresponding warning information, it evaluates and analyzes the urgency of replacing the photovoltaic power generation equipment, and determines whether to generate a replacement alarm signal through analysis, and sends the replacement alarm signal to the remote monitoring end.

[0034] Furthermore, the specific analysis process of the replacement evaluation decision module is as follows:

[0035] The operation time of photovoltaic power generation equipment is collected and marked as the operation condition value, and the total number of failures and the total amount of money invested in maintenance and inspection of photovoltaic power generation equipment in the past year are collected and marked as the failure frequency inspection value and the maintenance and inspection investment value respectively, and the benefit amount brought by the electricity produced by photovoltaic power generation equipment in the past year is collected and marked as the power generation benefit value;

[0036] The replacement assessment coefficient is obtained by numerically calculating the operation status value, fault frequency detection value, maintenance and inspection investment value and power generation benefit value, and the replacement assessment coefficient is numerically compared with the preset replacement assessment coefficient threshold. If the replacement assessment coefficient exceeds the preset replacement assessment coefficient threshold, a replacement alarm signal is generated.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. In the present invention, the stability status of the photovoltaic power generation equipment is detected and analyzed through the power generation equipment stability detection module, the power generation anomaly of the photovoltaic power generation equipment is analyzed when the stability qualified signal is generated, and the light tracking operation performance of the photovoltaic power generation equipment is analyzed when the power generation safety signal is generated. The stability status, power risk and light tracking performance of the photovoltaic power generation equipment can be accurately analyzed step by step and timely warned, and the targeted monitoring and reasonable operation and maintenance control of the photovoltaic power generation equipment can be realized, which is conducive to ensuring the safe, stable and efficient operation of the photovoltaic power generation equipment, and significantly reducing the management difficulty of the supervisory personnel;

[0039] 2. In the present invention, the generated warning information is sent to the replacement evaluation decision module through the operation and maintenance warning control module. When the replacement evaluation decision module receives the warning information, it evaluates and analyzes the urgency of replacing the photovoltaic power generation equipment, and eliminates the corresponding photovoltaic power generation equipment when a replacement alarm signal is generated, thereby effectively avoiding the operating losses caused by the corresponding photovoltaic power generation equipment, facilitating the supervisory personnel to make reasonable disposal measures for the corresponding photovoltaic power generation equipment, further reducing the difficulty of managing the photovoltaic power generation equipment, and having a high degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0041] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0042] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0043] 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.

[0044] Embodiment 1: Figure 1 As shown, the present invention proposes a distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system, including a power generation equipment stability detection module, a power anomaly analysis module, a light tracking analysis module, an operation and maintenance early warning control module and a remote supervision terminal;

[0045] The power generation equipment stability detection module detects and analyzes the stability status of the photovoltaic power generation equipment, generates a stability risk signal or a stability qualified signal based on it, and sends the stability risk signal to the operation and maintenance early warning control module, which can accurately determine the stability risk level of the photovoltaic power generation equipment and issue a timely early warning to remind the supervisory personnel to carry out operation and maintenance in time to ensure the operational stability of the photovoltaic power generation equipment; the specific analysis process of the photovoltaic equipment stability detection module is as follows:

[0046] The shaking frequency and shaking amplitude of the photovoltaic power generation equipment are collected in real time, and the shaking frequency and shaking amplitude are numerically compared with the preset shaking frequency threshold and the preset shaking amplitude threshold respectively. If the shaking frequency or shaking amplitude exceeds the corresponding preset threshold, it indicates that the shaking of the photovoltaic power generation equipment is severe, and it is judged that the photovoltaic power generation equipment is in an unstable state;

[0047] Obtain all single durations of the photovoltaic power generation equipment being in an unstable state within a unit time, sum up all single durations of the photovoltaic power generation equipment being in an unstable state within a unit time to obtain a total unstable time value, and mark the number of single durations exceeding the corresponding preset single duration threshold within a unit time as an unstable dangerous frequency value;

[0048] The total unstable time value and the unstable dangerous frequency value are numerically compared with the preset unstable total time threshold and the unstable dangerous frequency threshold, respectively. If the total unstable time value or the unstable dangerous frequency value exceeds the corresponding preset threshold, it indicates that the stability of the photovoltaic power generation equipment per unit time is poor, and a stability hidden danger signal is generated;

[0049] If the total unstable time value and the unstable risk frequency value do not exceed the corresponding preset threshold value, the support hidden danger coefficient is obtained through support hidden danger assessment analysis, specifically: the support structure of the photovoltaic power generation equipment is monitored, the sinking amount of the support structure compared with the initial time is collected and marked as the support sinking table value, and several detection points are set on the support structure, the real-time distance value between the corresponding two groups of detection points is collected and the deviation value from the corresponding initial distance value is marked as the point spacing deformation value;

[0050] The point spacing deformation value is numerically compared with the corresponding preset point spacing deformation threshold. If the point spacing deformation value exceeds the preset point spacing deformation threshold, it indicates that the deformation between the corresponding two groups of detection points is more serious, and the corresponding point spacing deformation value is marked as the point spacing abnormality value, and the number of point spacing abnormality values ​​is obtained and the ratio of the point spacing abnormality values ​​to the number of point spacing deformation values ​​is calculated to obtain the point spacing danger value; and the ratio of the point spacing deformation value to the corresponding preset point spacing deformation threshold is marked as the point spacing variation share value, and the average of all point spacing variation share values ​​is calculated to obtain the point spacing variation value;

[0051] The support hidden danger coefficient XP is obtained by numerically calculating the support sinking value XF, the point interval change risk value LW and the point interval change condition value NY through the formula XP=hg1*XF+(hg2*LW+hg3*NY) / hg1; wherein hg1, hg2 and hg3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the support hidden danger coefficient XP is, the worse the structural condition of the support structure of the photovoltaic power generation equipment is, and the greater the support stability hidden danger is in general;

[0052] The support hidden danger coefficient XP is numerically compared with the preset support hidden danger coefficient threshold. If the support hidden danger coefficient XP exceeds the preset support hidden danger coefficient threshold, it indicates that the structural condition of the supporting structure of the photovoltaic power generation equipment is poor, and the support stability hidden danger is generally large, then a stability hidden danger signal is generated; if the support hidden danger coefficient XP does not exceed the preset support hidden danger coefficient threshold, it indicates that the stability hidden danger of the photovoltaic power generation equipment is generally small, then a stability qualified signal is generated.

[0053] The power generation equipment stability detection module sends a stable qualified signal to the power anomaly analysis module. When the power anomaly analysis module receives the stable qualified signal, it analyzes the power generation anomaly of the photovoltaic power generation equipment, and generates a power generation warning signal or a power generation safety signal based on it, and sends the power generation warning signal to the operation and maintenance warning control module, which can accurately assess the power risk of the photovoltaic power generation equipment and issue a timely warning to remind the supervisory personnel to carry out operation and maintenance in time, which is conducive to ensuring the operation safety and efficiency of the photovoltaic power generation equipment. The specific analysis process of the power anomaly analysis module is as follows:

[0054] The voltage curve and current curve of the photovoltaic power generation equipment per unit time are obtained, and the voltage curve and the current curve are placed in the first quadrant of the corresponding rectangular coordinate system (where the X-axis of the rectangular coordinate system represents time and the Y-axis represents voltage / current), and all turning points on the voltage curve are obtained. The ratio of the Y-direction distance value between two adjacent groups of turning points to the corresponding X-direction distance value is marked as the pressure change coefficient, and the rheological coefficient is obtained in the same way;

[0055] The number of pressure variation coefficients exceeding the preset pressure variation coefficient threshold value per unit time is obtained and marked as the pressure variation test value, and the number of flow coefficients exceeding the preset flow coefficient threshold value per unit time is marked as the flow variation test value; and the Y-direction distance value between the highest point and the lowest point on the voltage curve per unit time is marked as the pressure amplitude measurement value, and the flow amplitude measurement value is obtained similarly;

[0056] By formula The voltage variation detection value TX, the flow variation detection value TF, the voltage amplitude measurement value TS and the flow amplitude measurement value TP are numerically calculated to obtain the power abnormality evaluation value QL; wherein up1, up2, up3, up4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the power abnormality evaluation value QL is, the more abnormal the fluctuation of the voltage and current of the photovoltaic power generation equipment is;

[0057] The power abnormality evaluation value QL is numerically compared with the preset power abnormality evaluation threshold. If the power abnormality evaluation value QL exceeds the preset power abnormality evaluation threshold, it indicates that the voltage and current fluctuations of the photovoltaic power generation equipment are abnormal, and a power generation warning signal is generated.

[0058] Furthermore, if the power abnormal evaluation value QL does not exceed the preset power abnormal evaluation threshold, the deviation value of the real-time grounding resistance value of the photovoltaic power generation equipment compared with the preset standard grounding resistance value is marked as the grounding resistance deviation value, and the deviation value of the real-time insulation resistance value of the photovoltaic power generation equipment compared with the preset standard insulation resistance value is marked as the insulation resistance deviation value;

[0059] And all the grounding resistance deviation values ​​within a unit time are averaged to obtain the grounding resistance table value, and all the insulation resistance deviation values ​​within a unit time are averaged to obtain the insulation resistance table value; and the actual power generation and electric energy output value of the photovoltaic power generation equipment within a unit time are collected, and the ratio of the electric energy output value to the actual power generation is marked as the power generation output table value;

[0060] By formula The power abnormal evaluation value QL, the grounding resistance meter value QW, the insulation resistance meter value QY and the power output meter value QN are numerically calculated to obtain the power warning value NF; wherein, se1, se2, se3, and se4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the power warning value NF is, the worse the power condition of the photovoltaic power generation equipment is in general;

[0061] The power warning value NF is numerically compared with the preset power warning threshold. If the power warning value NF exceeds the preset power warning threshold, it indicates that the power condition of the photovoltaic power generation equipment is generally poor, and a power generation warning signal is generated; if the power warning value NF does not exceed the preset power warning threshold, it indicates that the power condition of the photovoltaic power generation equipment is generally good, and a power generation safety signal is generated.

[0062] It should be noted that during the photovoltaic power generation process, the photovoltaic power generation equipment will automatically adjust the tilt angle based on the light direction to achieve automatic light tracking; the power anomaly analysis module sends the power generation safety signal to the light tracking analysis module. When the light tracking analysis module receives the power generation safety signal, it analyzes the light tracking operation performance of the photovoltaic power generation equipment per unit time, and generates a light tracking qualified signal or a light tracking abnormal signal through analysis, and sends the light tracking abnormal signal to the operation and maintenance early warning control module, which can reasonably analyze and accurately evaluate the light tracking execution performance of the photovoltaic power generation equipment, so as to remind the supervisors to carry out corresponding operation and maintenance processing for the photovoltaic power generation equipment in a timely manner, which is conducive to ensuring the power generation efficiency of the photovoltaic power generation equipment and significantly reducing the management difficulty of the supervisors; the specific analysis process of the light tracking analysis module is as follows:

[0063] The actual tilt angle of the photovoltaic power generation equipment is collected, and the deviation value between the actual tilt angle and the corresponding preset standard tilt angle is marked as a tilt detection value. The tilt detection value is numerically compared with a preset tilt detection threshold. If the tilt detection value exceeds the preset tilt detection threshold, it indicates that the current tilt angle of the photovoltaic power generation equipment does not meet the requirements, and the corresponding tilt detection value is marked as a tilt deviation value;

[0064] The number of inclination deviation values ​​per unit time is obtained and the ratio is calculated with the number of inclination detection values ​​to obtain the inclination abnormality value, and the average of all inclination detection values ​​per unit time is calculated to obtain the inclination analysis value; the inclination abnormality value and the inclination analysis value are numerically compared with the preset inclination abnormality threshold and the preset inclination analysis threshold, respectively. If the inclination abnormality value or the inclination analysis value exceeds the corresponding preset threshold, indicating that the light tracking performance of the photovoltaic power generation equipment is generally poor, a light tracking abnormality signal is generated.

[0065] Furthermore, if the tilt angle abnormality value and the tilt angle detection value do not exceed the corresponding preset threshold value, then when the photovoltaic power generation equipment adjusts the tilt angle, the average value and variance value of the adjustment speed of the corresponding adjustment process are collected and marked as the adjustment speed value and the adjustment speed wave value, respectively, and the average value of the noise decibel value generated in the corresponding adjustment process is marked as the adjustment noise value, and the deviation value of the adjustment speed value from the corresponding preset standard adjustment speed value is marked as the adjustment speed abnormality value;

[0066] The adjustment speed difference value GY, the adjustment speed wave value HD and the adjustment noise condition value ZY are numerically calculated by the formula ZF=(b1*GY+b2*HD+b3*ZY) / 3 to obtain the adjustment table evaluation value ZF; wherein, b1, b2 and b3 are preset proportional coefficients whose values ​​are greater than zero, and the larger the value of the adjustment table evaluation value ZF is, the worse the adjustment performance of the corresponding adjustment process of the photovoltaic power generation equipment is in general; the adjustment table evaluation value ZF is numerically compared with the preset adjustment table evaluation threshold value, and if the adjustment table evaluation value ZF exceeds the preset adjustment table evaluation threshold value, it indicates that the adjustment performance of the corresponding adjustment process of the photovoltaic power generation equipment is in general poor, and the corresponding adjustment process is marked as an adjustment difference process;

[0067] The number of adjustment processes per unit time is obtained and the ratio is calculated with the total number of adjustment processes to obtain the adjustment detection value, and the adjustment table evaluation values ​​of all adjustment processes per unit time are averaged to obtain the adjustment analysis value, and the adjustment detection value and the adjustment analysis value are numerically compared with the preset adjustment detection threshold and the preset adjustment analysis threshold respectively. If the adjustment detection value or the adjustment analysis value exceeds the corresponding preset threshold, it indicates that the light tracking adjustment condition of the photovoltaic power generation equipment is generally abnormal, and a light tracking abnormal signal is generated; if both the adjustment detection value and the adjustment analysis value do not exceed the corresponding preset threshold, it indicates that the light tracking adjustment condition of the photovoltaic power generation equipment is generally normal, and a light tracking qualified signal is generated.

[0068] It should be noted that when the operation and maintenance warning control module receives a stability hidden danger signal, a power generation warning signal or a light tracking abnormality signal, it generates corresponding warning information and sends the generated warning information to the remote monitoring end, which displays the corresponding warning information and issues a warning.

[0069] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the operation and maintenance warning control module is connected to the replacement evaluation decision module in communication, and the operation and maintenance warning control module sends the generated warning information to the replacement evaluation decision module. When the replacement evaluation decision module receives the corresponding warning information, it evaluates and analyzes the urgency of replacing the photovoltaic power generation equipment, and determines whether to generate a replacement alarm signal through analysis;

[0070] And the replacement alarm signal is sent to the remote monitoring end. When the remote monitoring end receives the replacement alarm signal, it issues a corresponding warning. When the supervisor receives the corresponding warning, he can eliminate the corresponding photovoltaic power generation equipment as needed, effectively avoiding the operating losses caused by the corresponding photovoltaic power generation equipment, which is conducive to the supervisor to make reasonable disposal measures for the corresponding photovoltaic power generation equipment, reducing the difficulty of managing photovoltaic power generation equipment, and has a high degree of intelligence; the specific analysis process of the replacement evaluation decision module is as follows:

[0071] The operation time of photovoltaic power generation equipment is collected and marked as the operation condition value, and the total number of failures and the total amount of money invested in maintenance and inspection of photovoltaic power generation equipment in the past year are collected and marked as the failure frequency inspection value and the maintenance and inspection investment value respectively, and the benefit amount brought by the electricity produced by photovoltaic power generation equipment in the past year is collected and marked as the power generation benefit value;

[0072] The replacement evaluation coefficient HL is obtained by numerically calculating the operation condition value HN, the fault frequency detection value SM, the maintenance investment value WN and the power generation benefit value XW through the formula HL=(rw1*HN+rw2*SM+rw3*WN) / (3.862+rw4*XW), wherein rw1, rw2, rw3 and rw4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the replacement evaluation coefficient HL is, the smaller the value of the corresponding photovoltaic power generation equipment is in continued use;

[0073] The replacement assessment coefficient HL is numerically compared with the preset replacement assessment coefficient threshold. If the replacement assessment coefficient HL exceeds the preset replacement assessment coefficient threshold, it indicates that the value of the corresponding photovoltaic power generation equipment continuing to be put into use is small, and a replacement alarm signal is generated.

[0074] The working principle of the present invention is as follows: when in use, the stability status of the photovoltaic power generation equipment is detected and analyzed through the power generation equipment stability detection module to accurately determine the degree of stability risk of the photovoltaic power generation equipment; when a stable qualified signal is generated, the power anomaly analysis module is used to analyze the power generation anomaly of the photovoltaic power generation equipment to accurately evaluate the power risk of the photovoltaic power generation equipment; and when a power generation safety signal is generated, the light tracking operation performance of the photovoltaic power generation equipment is analyzed through the light tracking analysis module to accurately output the light tracking execution status of the photovoltaic power generation equipment. The stability status, power risk and light tracking performance of the photovoltaic power generation equipment can be accurately analyzed step by step and in a progressive manner, and timely early warning can be given, so as to realize targeted monitoring of the photovoltaic power generation equipment, which is conducive to the reasonable operation and maintenance control of the photovoltaic power generation equipment, and ensure the safe, stable and efficient operation of the photovoltaic power generation equipment, significantly reduce the management difficulty of the supervisory personnel, and has a high degree of intelligence.

[0075] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system, characterized in that: It includes a power generation equipment stability detection module, a power anomaly analysis module, a light tracking analysis module, an operation and maintenance early warning control module and a remote monitoring terminal; the power generation equipment stability detection module detects and analyzes the stability status of the photovoltaic power generation equipment, generates a stability hidden danger signal or a stability qualified signal, and sends the stability hidden danger signal to the operation and maintenance early warning control module, and sends the stability qualified signal to the power anomaly analysis module; When the power anomaly analysis module receives the stable qualified signal, it analyzes the power generation anomaly of the photovoltaic power generation equipment, generates a power generation warning signal or a power generation safety signal accordingly, and sends the power generation warning signal to the operation and maintenance warning control module, and sends the power generation safety signal to the light tracking analysis module; The photovoltaic power generation equipment automatically adjusts its tilt angle based on the direction of light. When the light tracking analysis module receives the power generation safety signal, it analyzes the light tracking operation performance of the photovoltaic power generation equipment per unit time, generates a light tracking qualified signal or a light tracking abnormal signal through analysis, and sends the light tracking abnormal signal to the operation and maintenance early warning control module; The operation and maintenance warning control module generates corresponding warning information when receiving a stability hidden danger signal, a power generation warning signal or a light tracking abnormality signal, and sends the generated warning information to the remote monitoring terminal for display.

2. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 1, characterized in that: The specific analysis process of the photovoltaic equipment stability detection module includes: If the total unstable time value or the unstable risk frequency value exceeds the corresponding preset threshold, a stable hidden danger signal is generated; if both the total unstable time value and the unstable risk frequency value do not exceed the corresponding preset threshold, a support hidden danger evaluation analysis is performed to obtain the support hidden danger coefficient. If the support hidden danger coefficient exceeds the preset support hidden danger coefficient threshold, a stable hidden danger signal is generated; otherwise, a stable qualified signal is generated.

3. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 2, characterized in that: The specific analysis process supporting hidden danger assessment and analysis is as follows: The supporting structure of the photovoltaic power generation equipment is monitored, and the sinking amount of the supporting structure compared to the initial value is collected and marked as the support sinking table value. The support hidden danger coefficient is obtained by numerically calculating the support sinking table value, point interval hazard value and point interval condition value.

4. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 1, characterized in that: The specific analysis process of the power anomaly analysis module is as follows: The power abnormality evaluation value is obtained by numerically calculating the pressure variation detection value, flow variation detection value, pressure amplitude measurement value and flow amplitude measurement value. If the power abnormality evaluation value exceeds the preset power abnormality evaluation threshold, a power generation warning signal is generated.

5. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 4, characterized in that: If the power abnormality value does not exceed the preset power abnormality threshold, the power abnormality value, ground resistance meter value, insulation resistance meter value and power generation output meter value are numerically calculated to obtain the power warning value. If the power warning value exceeds the preset power warning threshold, a power generation early warning signal is generated; otherwise, a power generation safety signal is generated.

6. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 1, characterized in that: The specific analysis process of the light tracing analysis module includes: The actual tilt angle of the photovoltaic power generation equipment is collected, and the deviation value between the actual tilt angle and the corresponding preset standard tilt angle is marked as a tilt detection value. If the tilt detection value exceeds a preset tilt detection threshold, the corresponding tilt detection value is marked as a tilt deviation value; The number of inclination deviation values ​​per unit time is obtained and the ratio thereof is calculated with the number of inclination detection values ​​to obtain the inclination deviation value, and the average of all inclination detection values ​​per unit time is calculated to obtain the inclination detection value; if the inclination deviation value or the inclination detection value exceeds the corresponding preset threshold, a light tracking abnormality signal is generated.

7. A distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 6, characterized in that: If the inclination anomaly value and the inclination analysis value do not exceed the corresponding preset threshold value, the adjustment anomaly detection value and the adjustment analysis value will be numerically compared with the preset adjustment anomaly detection threshold value and the preset adjustment analysis threshold value respectively. If the adjustment anomaly detection value or the adjustment analysis value exceeds the corresponding preset threshold value, a light tracking abnormality signal is generated; otherwise, a light tracking qualified signal is generated.

8. The distributed photovoltaic power generation equipment intelligent operation and maintenance supervision and control system according to claim 1 is characterized in that: The operation and maintenance warning control module is communicatively connected to the replacement evaluation decision module. The operation and maintenance warning control module sends the generated warning information to the replacement evaluation decision module. The replacement evaluation decision module compares the replacement evaluation coefficient with the preset replacement evaluation coefficient threshold. If the replacement evaluation coefficient exceeds the preset replacement evaluation coefficient threshold, a replacement alarm signal is generated and sent to the remote monitoring end.

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