Photovoltaic support operation and maintenance management monitoring device

Abstract

The invention belongs to the technical field of photovoltaic power generation, and particularly relates to a photovoltaic support operation and maintenance management monitoring device comprising a sensor module used for collecting photovoltaic support data and photovoltaic support environment data and comprising a temperature sensor, a humidity sensor, a tuyere meteorological instrument, a tilt angle sensor and a pressure sensor; the data preprocessing and transmitting module is used for preprocessing the data acquired by each sensor and equipment in the sensor module and uploading the data to the operation and maintenance management monitoring module; the operation and maintenance management monitoring module is used for receiving the data uploaded by the data preprocessing transmission module and storing, monitoring, analyzing and displaying the data; and the early warning and diagnosis module is used for setting a threshold value and carrying out early warning and diagnosis on abnormal data. According to the photovoltaic support operation and maintenance management monitoring device provided by the invention, manual inspection is reduced, real-time monitoring of the state of the photovoltaic support is realized, timeliness and accuracy of operation and maintenance management are improved, and safe operation of a photovoltaic power station is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic power generation, and in particular relates to a photovoltaic support operation and maintenance management monitoring device. Background Art

[0002] With the continuous development of photovoltaic power generation technology, the number and scale of photovoltaic power stations are also gradually increasing. As an important part of photovoltaic power stations, the operating status of photovoltaic brackets directly affects the power generation efficiency and safe and stable operation of photovoltaic power stations. However, the traditional operation and maintenance management of photovoltaic brackets mainly relies on manual inspections and regular maintenance, which is time-consuming, labor-intensive, inefficient, and costly. Therefore, there is an urgent need for a photovoltaic bracket operation and maintenance management monitoring device that can monitor the operating status of photovoltaic brackets in real time and improve the efficiency of operation and maintenance management. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention provides a photovoltaic support operation and maintenance management and monitoring device.

[0004] The present invention is achieved through the following technical solutions:

[0005] A photovoltaic support operation and maintenance management and monitoring device is provided, the device comprising:

[0006] Sensor module: used to collect photovoltaic support data and photovoltaic support environment data, including temperature sensor, humidity sensor, wind outlet meteorological instrument, pressure sensor and tilt sensor; the temperature sensor is used to collect the working temperature data of the photovoltaic support, the humidity sensor is used to collect the environmental humidity data of the photovoltaic support, the wind outlet meteorological instrument is used to collect the wind force data of the photovoltaic support environment, the pressure sensor is used to collect the wind load data borne by the photovoltaic support, and the tilt sensor is used to collect the tilt data of the photovoltaic support center column; among them, the temperature sensor, humidity sensor and wind outlet meteorological instrument are installed on the photovoltaic support project site, the pressure sensor is installed on the photovoltaic support, and the tilt sensor is installed on the photovoltaic support center column;

[0007] Data preprocessing and transmission module: used to preprocess the data collected by each sensor and device in the sensor module and upload it to the operation and maintenance management monitoring module;

[0008] Operation and maintenance management monitoring module: used to receive data uploaded by the data preprocessing transmission module, and store, monitor, analyze and display the data;

[0009] Early warning and diagnosis module: used to set thresholds. When the operating temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the thresholds, early warning and diagnosis will be performed.

[0010] Preferably, the data preprocessing transmission module includes:

[0011] Missing value filling unit: used to process missing values ​​in the data. It uses the mean filling method to calculate the average value of all non-missing values ​​and fill the missing values ​​in the data with the calculated average value.

[0012] Noise filtering unit: used to identify and process outliers and noise in the data after missing value filling;

[0013] Communication unit: used to upload the pre-processed data to the operation and maintenance management monitoring module.

[0014] Preferably, the noise filtering unit uses a KNN algorithm to identify and process outliers in the data, including:

[0015] Select K value: K value represents the number of nearest neighbors, and K value is determined by cross-validation method;

[0016] Calculate the distance: Calculate the distance between each data point and other data points based on the Euclidean distance. The calculation formula is shown in formula (1):

[0017]

[0018] Among them, n is the dimension of the feature, x i,k and x j,k The data points x are i and x j The value of the kth feature;

[0019] Identify outliers: When the average distance between a data point and its K neighbors is greater than the set threshold, it is marked as an outlier. i ) is calculated as shown in formula (2):

[0020]

[0021] in, is the data point x i The K neighbors of x j is one of the K neighbors, and then calculate the average distance of all data points and standard deviation σ D , the calculation formula is shown in formula (3) and formula (4):

[0022]

[0023] Where N is the total number of data points, and the calculation formula of the threshold T is shown in formula (5):

[0024]

[0025] Where z is a constant, usually 2 or 3.i )>T, at this time x i Data points that are considered outliers are marked;

[0026] Handling outliers: Remove the marked outlier data points from the data.

[0027] Preferably, the operation and maintenance management monitoring module includes:

[0028] Micro-meteorological online monitoring unit: used to receive and monitor the working temperature data, environmental humidity data and wind data of the photovoltaic bracket in the data uploaded by the data preprocessing transmission module, where the wind data includes wind size data and wind direction data;

[0029] Wind load monitoring unit: used to receive and monitor the wind load data borne by the photovoltaic bracket in the data uploaded by the data preprocessing transmission module;

[0030] Inclination monitoring unit: used to receive and monitor the inclination data of the photovoltaic support center column in the data uploaded by the data preprocessing transmission module, and observe the status of the center column in real time;

[0031] Storage unit: used to store data received by the operation and maintenance management monitoring module;

[0032] Display unit: used to display the data received by the operation and maintenance management monitoring module on the monitoring screen.

[0033] Preferably, the early warning diagnosis module includes:

[0034] Threshold setting unit: used to set the working temperature threshold and environmental humidity threshold of the photovoltaic bracket; used to set the threshold of the wind load that the photovoltaic bracket can withstand; used to set the threshold of the inclination angle of the center column of the photovoltaic bracket;

[0035] Early warning unit: used to issue an early warning when the operating temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the threshold;

[0036] Diagnostic unit: used to diagnose the cause of exceeding the threshold and provide corresponding solutions when the working temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the threshold.

[0037] The advantages and effects of the present invention are:

[0038] The device of the present invention realizes real-time monitoring of the operating status of the photovoltaic support, and improves the timeliness and accuracy of operation and maintenance management. In addition, it also reduces the labor cost of operation and maintenance management, so that the operation and maintenance personnel can understand the real-time status of the photovoltaic support through the monitoring center without rushing to the photovoltaic support site, reducing the frequency and intensity of manual inspections, improving the convenience and efficiency of operation and maintenance, and ensuring the safe operation of the photovoltaic power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 This is a structural diagram of a photovoltaic support operation and maintenance management and monitoring device of the present invention.

[0041] Figure 2 The flowchart of the KNN algorithm of the present invention for identifying and processing outliers in data. DETAILED DESCRIPTION

[0042] 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.

[0043] The present invention provides a photovoltaic support operation and maintenance management monitoring device, such as Figure 1 As shown, including:

[0044] Sensor module: used to collect photovoltaic support data and photovoltaic support environment data, including temperature sensor, humidity sensor, wind outlet meteorological instrument, pressure sensor and tilt sensor; the temperature sensor is used to collect the working temperature data of the photovoltaic support, the humidity sensor is used to collect the environmental humidity data of the photovoltaic support, the wind outlet meteorological instrument is used to collect the wind force data of the photovoltaic support environment, the pressure sensor is used to collect the wind load data borne by the photovoltaic support, and the tilt sensor is used to collect the tilt data of the photovoltaic support center column; among them, the temperature sensor, humidity sensor and wind outlet meteorological instrument are installed on the photovoltaic support project site, the pressure sensor is installed on the photovoltaic support, and the tilt sensor is installed on the photovoltaic support center column;

[0045] Data preprocessing and transmission module: used to preprocess the data collected by each sensor and device in the sensor module and upload it to the operation and maintenance management monitoring module;

[0046] Operation and maintenance management monitoring module: used to receive data uploaded by the data preprocessing transmission module, and store, monitor, analyze and display the data;

[0047] Early warning and diagnosis module: used to set thresholds. When the operating temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the thresholds, early warning and diagnosis will be performed.

[0048] Among them, the data preprocessing transmission module includes:

[0049] Missing value filling unit: used to process missing values ​​in the data. It uses the mean filling method to calculate the average value of all non-missing values ​​and fill the missing values ​​in the data with the calculated average value.

[0050] Noise filtering unit: used to identify and process outliers and noise in the data after missing value filling;

[0051] Communication unit: used to upload the pre-processed data to the operation and maintenance management monitoring module.

[0052] Specifically, the KNN algorithm is used in the noise filtering unit to identify and process outliers in the data. The process is as follows: Figure 2 As shown, including:

[0053] Select K value: K value indicates the number of nearest neighbors. It is very important to select a suitable K value, because a K value that is too small may lead to overfitting, while a K value that is too large may ignore the local structure. In the present invention, the K value is determined by a cross-validation method;

[0054] Calculate the distance: Calculate the distance between each data point and other data points based on the Euclidean distance. The calculation formula is shown in formula (1):

[0055]

[0056] Among them, n is the dimension of the feature, x i,k and x j,k The data points x are i and x j The value of the kth feature;

[0057] Identify outliers: When the average distance between a data point and its K neighbors is greater than the set threshold, it is marked as an outlier. i ) is calculated as shown in formula (2):

[0058]

[0059] in, is the data point x i The K neighbors of x j is one of the K neighbors, and then calculate the average distance of all data points and standard deviation σ D , the calculation formula is shown in formula (3) and formula (4):

[0060]

[0061]

[0062] Where N is the total number of data points, and the calculation formula of the threshold T is shown in formula (5):

[0063]

[0064] Where z is a constant, usually 2 or 3. i )>T, at this time x i Data points that are considered outliers are marked;

[0065] Handling outliers: Remove the marked outlier data points from the data.

[0066] Specifically, the operation and maintenance management monitoring module includes:

[0067] Micro-meteorological online monitoring unit: used to receive and monitor the working temperature data, environmental humidity data and wind data of the photovoltaic bracket in the data uploaded by the data preprocessing transmission module, where the wind data includes wind size data and wind direction data;

[0068] Wind load monitoring unit: used to receive and monitor the wind load data borne by the photovoltaic bracket in the data uploaded by the data preprocessing transmission module;

[0069] Inclination monitoring unit: used to receive and monitor the inclination data of the photovoltaic support center column in the data uploaded by the data preprocessing transmission module, and observe the status of the center column in real time;

[0070] Storage unit: used to store data received by the operation and maintenance management monitoring module;

[0071] Display unit: used to display the data received by the operation and maintenance management monitoring module on the monitoring screen.

[0072] Specifically, the early warning diagnosis module includes:

[0073] Threshold setting unit: used to set the working temperature threshold and environmental humidity threshold of the photovoltaic bracket; used to set the threshold of the wind load that the photovoltaic bracket can withstand; used to set the threshold of the inclination angle of the center column of the photovoltaic bracket;

[0074] Early warning unit: used to issue an early warning when the operating temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the threshold;

[0075] Diagnostic unit: used to diagnose the cause of exceeding the threshold value and provide corresponding solutions when the working temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the threshold value;

[0076] The operating temperature threshold of the photovoltaic bracket needs to comprehensively consider the tolerance of the photovoltaic panels, electrical components and structural materials, as well as the actual operation requirements of the system, including:

[0077] Temperature threshold of photovoltaic panels: The performance of photovoltaic panels is greatly affected by temperature. The maximum operating temperature of the photovoltaic panel operating temperature threshold set by the present invention is 80°C, and the minimum operating temperature is -30°C. When the maximum operating temperature is exceeded or when the minimum operating temperature is lower than the minimum operating temperature, the efficiency of the photovoltaic panel will be significantly reduced or even damaged;

[0078] Temperature threshold of electrical components: The inverter, controller and other electrical components in the photovoltaic support also have their own temperature thresholds. The maximum operating temperature of the inverter and other electrical components is usually between 50℃ and 60℃. If the temperature exceeds this, the components may overheat and shut down to prevent damage; the minimum operating temperature is usually between -20℃ and -40℃. If the temperature is lower than this, the components may not start or work properly.

[0079] Temperature threshold of structural materials: Photovoltaic brackets are usually made of metal materials (such as aluminum alloys and steel). These materials may undergo physical changes at extreme temperatures, affecting their structural stability. In high-temperature environments, metal materials may expand, affecting the structural stability of the bracket. Usually, the maximum temperature tolerance of metal materials is above 100°C, but in actual applications, long-term exposure to environments above 60°C should be avoided; in low-temperature environments, metal materials may become brittle, increasing the risk of fracture. Usually, the minimum temperature tolerance of metal materials is around -40°C, but in actual applications, long-term exposure to environments below -20°C should be avoided.

[0080] Similarly, the environmental humidity threshold of the photovoltaic bracket needs to comprehensively consider the tolerance of electrical components and structural materials, as well as the actual operation requirements of the system, including:

[0081] Humidity threshold of electrical components: Electrical components are sensitive to humidity. High humidity may cause short circuits, corrosion and other problems. The maximum relative humidity of most electrical components is between 90% and 95%. If the humidity exceeds this, condensation may occur on the components, causing short circuits or corrosion. The minimum relative humidity of electrical components is usually around 30%. If the humidity is lower than this, static electricity problems may occur.

[0082] Humidity threshold of structural materials: Metal materials are prone to rust in high humidity environments, affecting their structural stability. The maximum relative humidity that metal materials can tolerate is around 90%. Long-term exposure to high humidity environments may accelerate corrosion. The minimum relative humidity that metal materials can tolerate is usually around 30%. Humidity levels below this may cause the material to dry out and crack.

[0083] In addition, comprehensive considerations are needed to set thresholds, including geographical location, understanding the installation location of the photovoltaic bracket, including altitude, climate characteristics, etc.; historical meteorological data, obtaining the maximum and minimum temperature and humidity records of the area, which can be obtained through meteorological stations or historical meteorological data; photovoltaic bracket parameters, determining the specific parameters of photovoltaic panels, electrical components and structural materials.

[0084] Among them, setting the threshold of the wind load that the photovoltaic bracket can withstand is an important step to ensure the safe operation of the photovoltaic bracket under strong wind conditions. Wind load refers to the force generated by wind on the photovoltaic bracket, including horizontal force and vertical force. Reasonable setting of the wind load threshold can prevent the photovoltaic bracket from being deformed, damaged or even collapsed due to excessive wind load. The calculation formula of wind load is shown in formula (6):

[0085] F=0.5×C d ×A×ρ×V 2 (6)

[0086] Where, F is the wind load (unit: Newton, N), C d is the wind pressure coefficient, which depends on the shape and surface roughness of the photovoltaic bracket, and A is the windward area (unit: square meters m 2 ), ρ is the air density (unit: kilograms per cubic meter, kg / m 3 ), usually 1.225kg / m 3 , V is the wind speed (unit: meter / second, m / s).

[0087] According to the historical maximum wind speed data of the region, select an appropriate design wind speed. Usually, the design wind speed will be the maximum wind speed that will not be exceeded in more than 98% of the years. Based on the calculated wind load F, multiply it by a safety factor (usually between 1.5 and 2) as the wind load threshold F. y To ensure the safety of the photovoltaic bracket, the following is an example:

[0088] Assume that the windward area of ​​a photovoltaic bracket is A = 10m 2 , wind pressure coefficient C d =1.2, air density ρ = 1.225 kg / m 3 , design wind speed V = 30m / s, safety factor is 1.5, the calculation formula of wind load F is shown in formula (7):

[0089] F = 0.5 × 1.2 × 10 × 1.225 × 30 2 =6615(N)

[0090] When the safety factor is 1.5, F y =9922.5(N), when the safety factor is 2, F y =13230(N).

[0091] The threshold of the inclination angle of the photovoltaic support column is set to ensure the stability and safety of the photovoltaic support. The photovoltaic support column usually adopts a rocking column structure, which allows the column to tilt to a certain safe angle. When the angle is too large, the force on the bottom axle pin exceeds the limit, causing the axle pin to break. If the column tilts, it may cause uneven force on the photovoltaic panel, affect the power generation efficiency, and even cause damage to the support structure. Factors that need to be considered in setting the threshold of the inclination angle of the photovoltaic support column include:

[0092] Geographical location: the location where the photovoltaic bracket is installed, such as terrain characteristics and soil type;

[0093] Bracket design: the design parameters of the photovoltaic bracket, such as the height, diameter and material of the center column;

[0094] Environmental factors: historical meteorological data of the installation area, such as wind speed and earthquakes, which may affect the stability of the bracket;

[0095] After considering the above three factors, the maximum inclination angle of the center column is determined according to the design requirements and specifications of the photovoltaic bracket center column, which is usually 2° to 5°, and then multiplied by a safety factor, usually 2. When the determined maximum inclination angle is 2°, the inclination angle threshold of the photovoltaic bracket center column is 4°; when the determined maximum inclination angle is 5°, the inclination angle threshold of the photovoltaic bracket center column is 10°.

[0096] After setting the thresholds, when the operating temperature data, ambient humidity data, wind load data, and inclination data monitored by the operation and maintenance management monitoring module exceed the thresholds, early warning and diagnosis are performed. The early warning includes two levels:

[0097] Warning: The data monitored by the operation and maintenance management monitoring module is close to the set threshold but has not exceeded it;

[0098] Alarm: The data monitored by the operation and maintenance management monitoring module exceeds the threshold and immediate measures must be taken;

[0099] All warnings or alarms are issued through bright lights, alarm bells, and text messages to notify operation and maintenance personnel in a timely manner.

[0100] When the data exceeds the threshold, the system automatically performs fault diagnosis and analyzes possible causes. The following are some fault scenarios and diagnosed causes:

[0101] The maximum operating temperature of the photovoltaic panel exceeds the threshold: poor heat dissipation, high ambient temperature or photovoltaic panel failure;

[0102] The maximum relative humidity of electrical components exceeds the threshold: electrical components are poorly sealed in a humid environment;

[0103] The inclination angle of the photovoltaic support column exceeds the threshold: soil settlement, unstable support or external force.

[0104] The various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0105] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A photovoltaic support operation and maintenance management and monitoring device, characterized in that: The device comprises: Sensor module: used to collect photovoltaic support data and photovoltaic support environment data, including temperature sensor, humidity sensor, wind outlet meteorological instrument, pressure sensor and tilt sensor; the temperature sensor is used to collect the working temperature data of the photovoltaic support, the humidity sensor is used to collect the environmental humidity data of the photovoltaic support, the wind outlet meteorological instrument is used to collect the wind force data of the photovoltaic support environment, the pressure sensor is used to collect the wind load data borne by the photovoltaic support, and the tilt sensor is used to collect the tilt data of the photovoltaic support center column; among them, the temperature sensor, humidity sensor and wind outlet meteorological instrument are installed on the photovoltaic support project site, the pressure sensor is installed on the photovoltaic support, and the tilt sensor is installed on the photovoltaic support center column; Data preprocessing and transmission module: used to preprocess the data collected by each sensor and device in the sensor module and upload it to the operation and maintenance management monitoring module; Operation and maintenance management monitoring module: used to receive data uploaded by the data preprocessing transmission module, and store, monitor, analyze and display the data; Early warning and diagnosis module: used to set thresholds. When the operating temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the thresholds, early warning and diagnosis will be performed.

2. A photovoltaic support operation and maintenance management and monitoring device according to claim 1, characterized in that: The data preprocessing transmission module comprises: Missing value filling unit: used to process missing values ​​in the data. It uses the mean filling method to calculate the average value of all non-missing values ​​and fill the missing values ​​in the data with the calculated average value. Noise filtering unit: used to identify and process outliers and noise in the data after missing value filling; Communication unit: used to upload the pre-processed data to the operation and maintenance management monitoring module.

3. A photovoltaic support operation and maintenance management and monitoring device according to claim 2, characterized in that: The noise filtering unit uses the KNN algorithm to identify and process abnormal values ​​in the data, including: Select K value: K value represents the number of nearest neighbors, and K value is determined by cross-validation method; Calculate the distance: Calculate the distance between each data point and other data points based on the Euclidean distance. The calculation formula is shown in formula (1): Among them, n is the dimension of the feature, x i,k and x j,k The data points x are i and x j The value of the kth feature; Identify outliers: When the average distance between a data point and its K neighbors is greater than the set threshold, it is marked as an outlier. i ) is calculated as shown in formula (2): Among them, N K(xi) is the data point x i The K neighbors of x j is one of the K neighbors, and then calculate the average distance of all data points and standard deviation σ D , the calculation formula is shown in formula (3) and formula (4): Where N is the total number of data points, and the calculation formula of the threshold T is shown in formula (5): Where z is a constant. When D(x i )>T, at this time x i Data points that are considered outliers are marked; Handling outliers: Remove the marked outlier data points from the data.

4. A photovoltaic support operation and maintenance management and monitoring device according to claim 1, characterized in that: The operation and maintenance management monitoring module includes: Micro-meteorological online monitoring unit: used to receive and monitor the working temperature data, environmental humidity data and wind data of the photovoltaic bracket in the data uploaded by the data preprocessing transmission module, where the wind data includes wind size data and wind direction data; Wind load monitoring unit: used to receive and monitor the wind load data borne by the photovoltaic bracket in the data uploaded by the data preprocessing transmission module; Inclination monitoring unit: used to receive and monitor the inclination data of the photovoltaic support center column in the data uploaded by the data preprocessing transmission module, and observe the status of the center column in real time; Storage unit: used to store data received by the operation and maintenance management monitoring module; Display unit: used to display the data received by the operation and maintenance management monitoring module on the monitoring screen.

5. A photovoltaic support operation and maintenance management and monitoring device according to claim 1, characterized in that: The early warning diagnosis module includes: Threshold setting unit: used to set the working temperature threshold and environmental humidity threshold of the photovoltaic bracket; used to set the threshold of the wind load that the photovoltaic bracket can withstand; used to set the threshold of the inclination angle of the center column of the photovoltaic bracket; Early warning unit: used to issue an early warning when the operating temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the threshold; Diagnostic unit: used to diagnose the cause of exceeding the threshold and provide corresponding solutions when the working temperature data, environmental humidity data, wind load data and inclination data monitored by the operation and maintenance management monitoring module exceed the threshold.

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