Multimode-based photovoltaic inverter power distribution monitoring method and system

Abstract

The application relates to the field of photovoltaic power generation system monitoring, and relates to a photovoltaic inverter power distribution monitoring method and system based on multi-modalities, which comprises the following steps: confirming a photovoltaic inverter based on a power distribution monitoring instruction, confirming an electromagnetic monitoring mechanism, a temperature analysis mechanism and an environment monitoring mechanism, performing electromagnetic analysis on the photovoltaic inverter by using the electromagnetic monitoring mechanism to obtain an electromagnetic anomaly index, performing temperature image analysis on a semiconductor module by using the temperature analysis mechanism to obtain a temperature anomaly index, monitoring a device shell by using the environment monitoring mechanism to obtain an operation stability index, inputting the electromagnetic anomaly weight, the electromagnetic anomaly index, the temperature anomaly weight, the temperature anomaly index, the current environment weight and the operation stability index into a pre-constructed multi-modality monitoring model to obtain a power distribution anomaly degree, and completing power distribution monitoring of the photovoltaic inverter based on a danger monitoring end or a safety monitoring end. The application can improve the accuracy and automation degree of monitoring of the photovoltaic inverter.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation system monitoring, and in particular to a method and system for monitoring the power distribution of photovoltaic inverters based on multi-mode operation. Background Technology

[0002] With the continued growth in global demand for renewable energy, photovoltaic (PV) power generation systems are being used more and more widely in various buildings, industrial facilities, and grid connection scenarios. As the core equipment connecting PV modules and the grid, the PV inverter's operational stability and power distribution security have a decisive impact on the power generation efficiency and lifespan of the entire PV system.

[0003] Currently, most monitoring methods for photovoltaic inverters are based on single-mode or single-threshold data analysis methods, which issue alarms when parameters such as temperature or current exceed a certain threshold.

[0004] While existing methods can monitor the power distribution of photovoltaic inverters, single-mode data analysis can only assess local characteristics of the inverter and cannot perform correlation analysis on multiple interference factors such as electromagnetic disturbances, temperature rise risks, and environmental factors. This can easily lead to delayed fault warnings or misjudgments. Therefore, there is an urgent need for a monitoring method that can integrate multi-mode information. By integrating multi-mode data such as electromagnetic, temperature, and environmental data, a comprehensive assessment and intelligent judgment of the power distribution status of photovoltaic inverters can be achieved, thereby improving monitoring accuracy and fault response efficiency. Summary of the Invention

[0005] This invention provides a multi-mode photovoltaic inverter power distribution monitoring method and a computer-readable storage medium, the main purpose of which is to improve the accuracy and automation of photovoltaic inverter monitoring.

[0006] To achieve the above objectives, the present invention provides a multi-mode photovoltaic inverter power distribution monitoring method, comprising:

[0007] Receive power distribution monitoring instructions and identify the photovoltaic inverter based on the power distribution monitoring instructions. The photovoltaic inverter includes: device housing, photovoltaic input cable, power distribution output cable, semiconductor module, grounding device and heat sink.

[0008] The electromagnetic monitoring mechanism, temperature analysis mechanism, and environmental monitoring mechanism were identified. The electromagnetic monitoring mechanism includes: light sensor, humidity sensor, EMI monitor, current sensor, and resistance monitor. The temperature analysis mechanism includes: high-definition camera and infrared camera. The environmental monitoring mechanism includes: sound sensor and vibration sensor. The EMI monitor includes: test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing.

[0009] Electromagnetic anomaly weights are obtained by using a pre-built environmental database and electromagnetic monitoring institutions. Electromagnetic analysis of photovoltaic inverters is performed by electromagnetic monitoring institutions to obtain electromagnetic anomaly indices.

[0010] The temperature analysis mechanism is used to assess the condition of the heat sink and obtain the temperature anomaly weight. The temperature analysis mechanism is also used to analyze the temperature image of the semiconductor module and obtain the temperature anomaly index.

[0011] The current environmental weights are determined, and the environmental monitoring agency is used to monitor the device casing to obtain the operational stability index.

[0012] The electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operational stability index are input into the pre-built multimodal monitoring model to obtain the power distribution anomaly degree.

[0013] Compare the power distribution anomaly level with the preset anomaly threshold. If the power distribution anomaly level is greater than or equal to the anomaly threshold, the pre-built danger signal is sent to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, the pre-built safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal.

[0014] Power distribution monitoring of photovoltaic inverters is completed based on hazard monitoring terminals or safety monitoring terminals.

[0015] Optionally, obtaining electromagnetic anomaly weights using a pre-built environmental database and electromagnetic monitoring institutions includes:

[0016] The current time is determined, and the current time range is determined based on the current time and the preset reference duration;

[0017] Based on the current time range, multiple historical moment data are extracted from the environmental database. The historical moment data includes: historical light intensity and historical humidity.

[0018] Multiple historical light intensities and multiple historical humidity values ​​are extracted from data from multiple historical moments. The current reference light intensity is calculated based on the multiple historical light intensities, where the current reference light intensity is the average of the multiple historical light intensities.

[0019] Calculate the current reference humidity based on multiple historical humidity levels;

[0020] Based on preset monitoring intervals, preset monitoring times, and light and humidity sensors, multiple current light intensities and multiple current humidity levels are obtained.

[0021] The electromagnetic anomaly weight is calculated based on multiple current light intensities, multiple current humidity levels, current reference light intensity, and current reference humidity.

[0022] Optionally, the step of using an electromagnetic monitoring mechanism to perform electromagnetic analysis on the photovoltaic inverter to obtain an electromagnetic anomaly index includes:

[0023] The test antenna of the EMI monitor in the electromagnetic monitoring mechanism is raised and aligned to prepare the monitor;

[0024] Electromagnetic interference monitoring of photovoltaic inverters is performed based on preset monitoring frequency bands and prepared monitoring instruments to obtain electromagnetic spectrum curves, where the horizontal axis of the electromagnetic spectrum curve is frequency and the vertical axis of the electromagnetic spectrum curve is amplitude.

[0025] The monitoring frequency band is uniformly divided based on a preset frequency band interval to obtain multiple frequency ranges;

[0026] Perform the following operation for each of the multiple frequency ranges:

[0027] Based on the frequency range, the target spectrum curve is identified in the electromagnetic spectrum curve, and the maximum interference amplitude of the target spectrum curve is determined.

[0028] The maximum interference amplitude is summarized to obtain multiple maximum interference amplitudes. The average interference amplitude is calculated based on the multiple maximum interference amplitudes.

[0029] Based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism, the photovoltaic input cable in the photovoltaic inverter is monitored to obtain multiple input current values;

[0030] Based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism, the power distribution output cable in the photovoltaic inverter is monitored to obtain multiple output current values;

[0031] The mean and variance of the input current are calculated based on multiple input current values, and the mean and variance of the output current are obtained based on multiple output current values.

[0032] The grounding resistance is obtained by using a resistance monitor to detect the grounding device in the photovoltaic inverter;

[0033] The electromagnetic anomaly index is calculated based on the average interference amplitude, mean input current, variance of input current, mean output current, variance of output current, and grounding resistance.

[0034] Optionally, the formula for calculating the electromagnetic anomaly index is as follows:

[0035]

[0036] Where, ψ B Electromagnetic anomaly index, For the average interference amplitude, and These are the average input current and the average output current, respectively. and These are the preset reference input current value and the preset reference output current value, respectively. and These are the input current variance and the output current variance, respectively, R L Here, e represents the grounding resistance, and e is the natural constant.

[0037] Optionally, the step of using a temperature analysis mechanism to assess the condition of the radiator and obtain temperature anomaly weights includes:

[0038] The radiator surface is imaged using a high-definition camera in the temperature analysis unit.

[0039] The pre-constructed initial radiator image and radiator surface image are input into the pre-constructed image comparison model to obtain image similarity.

[0040] Calculate temperature anomaly weights using image similarity.

[0041] Optionally, the step of using a temperature analysis mechanism to perform temperature image analysis on the semiconductor module to obtain a temperature anomaly index includes:

[0042] Based on the monitoring interval, monitoring time, and temperature analysis mechanism, the infrared camera in the semiconductor module is used to capture multiple infrared temperature images. Each infrared temperature image includes multiple infrared pixels, and each infrared pixel includes an infrared temperature value.

[0043] For each of the multiple infrared temperature images, perform the following operation:

[0044] Calculate the average temperature based on multiple infrared pixels in the infrared temperature image;

[0045] Perform the following operation on each of the multiple infrared pixels in the infrared temperature image:

[0046] Compare the infrared temperature value corresponding to the infrared pixel with the preset temperature threshold;

[0047] If the infrared temperature value corresponding to an infrared pixel is greater than the temperature threshold, then the infrared pixel is recorded as an over-temperature pixel.

[0048] Summarize the over-temperature pixels to obtain multiple over-temperature pixels, and confirm the number of over-temperature pixels among the multiple over-temperature pixels. The number of over-temperature pixels is the number of over-temperature pixels among the multiple over-temperature pixels.

[0049] Calculate the overheat ratio based on the number of overheats;

[0050] The average temperature and overtemperature ratio corresponding to the infrared temperature images are combined to obtain the infrared data set;

[0051] By summing up the infrared data sets, multiple infrared data sets are obtained.

[0052] The temperature anomaly index was calculated based on multiple infrared data sets.

[0053] Optionally, determining the current environmental weight includes:

[0054] Confirm the current wind speed and current rainfall;

[0055] Calculate the current environmental weight using the current wind speed and current rainfall.

[0056] Optionally, the monitoring of the device casing by an environmental monitoring agency to obtain an operational stability index includes:

[0057] The sound sensor and vibration sensor in the environmental monitoring agency were used to monitor the device casing to obtain the internal noise intensity and casing vibration amplitude.

[0058] The operational stability index is calculated based on the internal noise intensity and the vibration amplitude of the casing.

[0059] Optionally, the multimodal monitoring model is as follows:

[0060]

[0061] Among them, Z G For distribution anomaly degree, ρ B For electromagnetic anomaly weights, ρ T For the weight of temperature anomalies, ρ E ψ represents the current environmental weight. T ψ is the temperature anomaly index. X The stability exponent is tanh, where tanh is the hyperbolic tangent function.

[0062] To achieve the above objectives, the present invention also provides a multi-mode photovoltaic inverter power distribution monitoring system, comprising:

[0063] The power distribution mechanism confirmation module is used to receive power distribution monitoring commands and confirm the photovoltaic inverter based on the commands. The photovoltaic inverter includes: a device housing, a photovoltaic input cable, a power distribution output cable, a semiconductor module, a grounding device, and a heat sink. The module also confirms the electromagnetic monitoring mechanism, the temperature analysis mechanism, and the environmental monitoring mechanism. The electromagnetic monitoring mechanism includes: a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The temperature analysis mechanism includes: a high-definition camera and an infrared camera. The environmental monitoring mechanism includes: a sound sensor and a vibration sensor. The EMI monitor includes: a test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing.

[0064] The modal data analysis module is used to obtain electromagnetic anomaly weights using a pre-built environmental database and electromagnetic monitoring mechanism, perform electromagnetic analysis on the photovoltaic inverter using the electromagnetic monitoring mechanism to obtain the electromagnetic anomaly index, perform state assessment on the heat sink using the temperature analysis mechanism to obtain the temperature anomaly weights, perform temperature image analysis on the semiconductor module using the temperature analysis mechanism to obtain the temperature anomaly index, confirm the current environmental weights, and monitor the device casing using the environmental monitoring mechanism to obtain the operating stability index.

[0065] The power distribution status assessment module is used to input electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operation stability index into a pre-built multimodal monitoring model to obtain the power distribution anomaly degree.

[0066] The monitoring signal alert module is used to compare the power distribution anomaly degree with the preset anomaly threshold. If the power distribution anomaly degree is greater than or equal to the anomaly threshold, a pre-built danger signal is sent to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, a pre-built safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal. Based on the danger monitoring terminal or the safety monitoring terminal, the power distribution monitoring of the photovoltaic inverter is completed.

[0067] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0068] Memory, storing at least one instruction;

[0069] The processor executes the instructions stored in the memory to implement the multi-mode photovoltaic inverter power distribution monitoring method described above.

[0070] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the multi-mode-based photovoltaic inverter power distribution monitoring method described above.

[0071] To address the problems described in the background art, this invention receives power distribution monitoring commands and identifies a photovoltaic inverter based on these commands. The photovoltaic inverter includes a device housing, a photovoltaic input cable, a power distribution output cable, a semiconductor module, a grounding device, and a heat sink. It also identifies an electromagnetic monitoring mechanism, a temperature analysis mechanism, and an environmental monitoring mechanism. The electromagnetic monitoring mechanism includes a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The temperature analysis mechanism includes a high-definition camera and an infrared camera. The environmental monitoring mechanism includes a sound sensor and a vibration sensor. The EMI monitor includes a test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing. As can be seen, this embodiment of the invention provides a systematic and automated monitoring environment for photovoltaic inverters by pre-constructing electromagnetic monitoring, temperature analysis, and environmental monitoring mechanisms. It then utilizes a pre-constructed environmental database and electromagnetic monitoring mechanisms to obtain electromagnetic anomaly weights, and uses the electromagnetic monitoring mechanisms to perform electromagnetic analysis on the photovoltaic inverters to obtain an electromagnetic anomaly index. This embodiment of the invention, by combining the environmental database and the monitoring results of the current electromagnetic monitoring mechanisms, performs electromagnetic analysis on the photovoltaic inverters, accurately confirming the degree of electrical performance anomalies and improving the accuracy of photovoltaic inverter monitoring. The temperature analysis mechanism is used to assess the condition of the heat sink and obtain temperature anomaly weights. The temperature analysis mechanism is also used to analyze the semiconductor modules... Temperature image analysis yields a temperature anomaly index. This embodiment of the invention utilizes a temperature analysis mechanism to simultaneously analyze images of the heat sink and semiconductor module, considering both the heat dissipation and heat generation states of the photovoltaic inverter, thus improving the accuracy of photovoltaic inverter monitoring. The current environmental weight is determined, and an environmental monitoring mechanism monitors the device casing to obtain an operational stability index. This embodiment of the invention, by fusing sound and vibration data and combining them with the current environmental conditions, accurately assesses the operational stability of the components within the photovoltaic inverter, improving the accuracy of photovoltaic inverter monitoring. Electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environmental weight, and operational stability index are input into a pre-constructed multimodal monitoring model. In this embodiment of the invention, the power distribution anomaly degree is obtained. It can be seen that the multi-modal monitoring model is used to perform correlation analysis on the electrical performance, temperature rise risk and operational stability of the photovoltaic inverter, thereby improving the accuracy of monitoring the photovoltaic inverter. The power distribution anomaly degree is compared with the preset anomaly threshold. If the power distribution anomaly degree is greater than or equal to the anomaly threshold, a pre-constructed danger signal is sent to the pre-constructed inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, a pre-constructed safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal. Based on the danger monitoring terminal or the safety monitoring terminal, the power distribution monitoring of the photovoltaic inverter is completed. It can be seen that the embodiment of the invention automatically sends danger signals or safety signals to the inverter monitoring terminal through the power distribution anomaly degree, thereby improving the fault response efficiency and the degree of automation of monitoring.Therefore, the present invention can improve the accuracy and automation of monitoring photovoltaic inverters. Attached Figure Description

[0072] Figure 1 This is a flowchart illustrating a multi-mode photovoltaic inverter power distribution monitoring method according to an embodiment of the present invention.

[0073] Figure 2 This is a functional block diagram of a multi-mode photovoltaic inverter power distribution monitoring system provided in an embodiment of the present invention;

[0074] Figure 3 This is a schematic diagram of the structure of an electronic device for implementing the multi-mode photovoltaic inverter power distribution monitoring method according to an embodiment of the present invention.

[0075] Explanation of reference numerals in the attached figures:

[0076] 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0077] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0078] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0079] This application provides a multi-modal photovoltaic inverter power distribution monitoring method. The executing entity of the multi-modal photovoltaic inverter power distribution monitoring method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the multi-modal photovoltaic inverter power distribution monitoring method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0080] Reference Figure 1 The diagram shown is a flowchart illustrating a multi-mode photovoltaic inverter power distribution monitoring method according to an embodiment of the present invention. In this embodiment, the multi-mode photovoltaic inverter power distribution monitoring method includes:

[0081] S1. Receive power distribution monitoring instructions and identify the photovoltaic inverter based on the power distribution monitoring instructions. The photovoltaic inverter includes: device housing, photovoltaic input cable, power distribution output cable, semiconductor module, grounding device and heat sink.

[0082] It should be explained that power distribution monitoring commands are generally initiated by monitors at the inverter monitoring center. For example, let's say Zhang is a monitor at an inverter monitoring center and needs to monitor a specific photovoltaic inverter. Therefore, he initiates the power distribution monitoring command. Since each photovoltaic inverter has a corresponding number or code in the inverter monitoring terminal of the inverter monitoring center, the photovoltaic inverter's number or code can be specified when initiating the power distribution monitoring command. This results in a power distribution monitoring command targeting only a specific photovoltaic inverter. The inverter monitoring center can then identify the corresponding photovoltaic inverter based on the photovoltaic inverter's number or code corresponding to the power distribution monitoring command. The inverter monitoring center is a department within a photovoltaic power plant used for monitoring photovoltaic inverters.

[0083] Understandably, a photovoltaic (PV) inverter includes: a housing, PV input cables, power output cables, semiconductor modules, a grounding system, and a heat sink. The housing is the structural outer shell used to enclose, support, and protect the internal components of the PV inverter. It is typically made of metal or high-strength composite materials to ensure the safety of the components in outdoor environments. The PV input cables are the wires that transmit the direct current generated by the photovoltaic devices (such as solar panels) to the PV inverter. The power output cables are the wires that output the converted alternating current from the PV inverter to the power grid or load. The semiconductor module refers to the IGBT (Insulated Gate Bipolar Transistor) module in the PV inverter. The grounding system is the grounding conductor in the PV inverter; its main function is to provide a low-impedance current discharge path in the event of insulation failure, leakage, or lightning strikes, ensuring the safety of the PV inverter. The heat sink is a device used to dissipate heat from the internal components of the PV inverter, including metal heat sinks, heat pipes, and air-cooled system blocks.

[0084] S2. Identify the electromagnetic monitoring mechanism, temperature analysis mechanism, and environmental monitoring mechanism. The electromagnetic monitoring mechanism includes: a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The temperature analysis mechanism includes: a high-definition camera and an infrared camera. The environmental monitoring mechanism includes: a sound sensor and a vibration sensor. The EMI monitor includes: a test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing.

[0085] It should be explained that the electromagnetic monitoring mechanism is a device integrating a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The light and humidity sensors are installed on the surface of the photovoltaic inverter's housing to monitor the relative humidity and light intensity of the external environment. The EMI monitor is an EMI test receiver, including a test antenna (a biconical antenna) for monitoring low-frequency (30MHz to 300MHz) electromagnetic interference signals generated by the photovoltaic inverter during operation. The EMI monitor is installed at a preset electromagnetic position, with the distance between this position and the photovoltaic inverter's center of gravity between 3 and 10 meters. This specific electromagnetic position is manually set by personnel at the inverter monitoring center. The current sensor is a clamp-on ammeter fixed to the photovoltaic input cable and power output cable of the photovoltaic inverter to monitor the current in these cables. The resistance monitor is a clamp-on grounding resistor installed on the photovoltaic inverter's grounding device to detect the resistance of the grounding device. The temperature analysis unit is a device integrating a high-definition camera and an infrared camera. The high-definition camera is a type of high-definition video camera, and the infrared camera is a type of infrared imager. The environmental monitoring unit is a device integrating a sound sensor and a vibration sensor. Both the sound sensor and the vibration sensor are mounted on the surface of the device housing, and are used to monitor the vibration amplitude of the device housing and the sound intensity of the noise inside the device housing, respectively.

[0086] S3. Obtain electromagnetic anomaly weights using a pre-built environmental database and electromagnetic monitoring institutions, and perform electromagnetic analysis on the photovoltaic inverter using electromagnetic monitoring institutions to obtain the electromagnetic anomaly index.

[0087] Specifically, the method of obtaining electromagnetic anomaly weights using a pre-built environmental database and electromagnetic monitoring institutions includes:

[0088] The current time is determined, and the current time range is determined based on the current time and the preset reference duration;

[0089] Based on the current time range, multiple historical moment data are extracted from the environmental database. The historical moment data includes: historical light intensity and historical humidity.

[0090] Multiple historical light intensities and multiple historical humidity values ​​are extracted from data from multiple historical moments. The current reference light intensity is calculated based on the multiple historical light intensities, where the current reference light intensity is the average of the multiple historical light intensities.

[0091] Calculate the current reference humidity based on multiple historical humidity levels;

[0092] Based on preset monitoring intervals, preset monitoring times, and light and humidity sensors, multiple current light intensities and multiple current humidity levels are obtained.

[0093] The electromagnetic anomaly weight is calculated based on multiple current light intensities, multiple current humidity levels, current reference light intensity, and current reference humidity. The calculation formula is as follows:

[0094]

[0095] Where, ρ B For electromagnetic anomaly weights, LX i S is the i-th current light intensity among multiple current light intensities. i Let i be the i-th current humidity among multiple current humidity values. and These are the current reference light intensity and the current reference humidity, respectively, and n is the number of current light intensities among multiple current light intensities.

[0096] It should be explained that "current moment" refers to the exact time at this moment. The minimum value of the current time range is the current moment minus the reference duration, and the maximum value is the current moment plus the reference duration. The environmental database stores multiple environmental data points monitored by the light and humidity sensors over a recent period. These environmental data consist of light intensity and relative humidity. Optionally, the recent period is 30 days, and the environmental database is pre-built by staff at the inverter monitoring center.

[0097] For example, if the current time is 10:00:00, then the current time is 10:00:00. If the reference duration is half an hour, then the current time range is [09:30:00, 10:30:00]. Therefore, multiple environmental data within the time period [09:30:00, 10:30:00] within 30 days are extracted from the environmental database. These multiple environmental data are used as multiple historical time data, and the historical time data includes: historical light intensity and historical humidity. The historical light intensity is the light intensity in the environmental data, and the historical humidity is the relative humidity in the environmental data.

[0098] It is understood that the method for calculating the current reference humidity based on multiple historical humidity levels is the same as the method for calculating the current reference light intensity based on multiple historical light intensities, and will not be described in detail here.

[0099] For example, if the monitoring interval is 1 second and the monitoring time is 10 seconds, then the light intensity and relative humidity in the current environment are obtained once every 1 second using the light sensor and humidity sensor, and finally 10 current light intensities and 10 current humidity values ​​are obtained. The current light intensity is the light intensity at the location where the light sensor is deployed, and the current humidity is the relative humidity of the air at the location where the humidity sensor is deployed. The monitoring interval and monitoring time are both manually set by the staff of the inverter monitoring center.

[0100] It should be understood that when the light intensity is too high, the output current generated by the photovoltaic modules under illumination increases, leading to an increase in the load on the input terminal of the photovoltaic inverter. When the humidity is too high, the insulation performance of the photovoltaic inverter or its terminals is more likely to deteriorate, increasing the probability of electrical faults such as short circuits or leakage. The electromagnetic anomaly weight reflects the degree of risk of electrical performance failure in the photovoltaic inverter. The higher the electromagnetic anomaly weight, the higher the risk of electrical performance failure in the photovoltaic inverter.

[0101] In detail, the electromagnetic analysis of the photovoltaic inverter using an electromagnetic monitoring mechanism to obtain an electromagnetic anomaly index includes:

[0102] The test antenna of the EMI monitor in the electromagnetic monitoring mechanism is raised and aligned to prepare the monitor;

[0103] Electromagnetic interference monitoring of photovoltaic inverters is performed based on preset monitoring frequency bands and prepared monitoring instruments to obtain electromagnetic spectrum curves, where the horizontal axis of the electromagnetic spectrum curve is frequency and the vertical axis of the electromagnetic spectrum curve is amplitude.

[0104] The monitoring frequency band is uniformly divided based on a preset frequency band interval to obtain multiple frequency ranges;

[0105] Perform the following operation for each of the multiple frequency ranges:

[0106] Based on the frequency range, the target spectrum curve is identified in the electromagnetic spectrum curve, and the maximum interference amplitude of the target spectrum curve is determined.

[0107] The maximum interference amplitude is summarized to obtain multiple maximum interference amplitudes. The average interference amplitude is calculated based on the multiple maximum interference amplitudes.

[0108] Based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism, the photovoltaic input cable in the photovoltaic inverter is monitored to obtain multiple input current values;

[0109] Based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism, the power distribution output cable in the photovoltaic inverter is monitored to obtain multiple output current values;

[0110] The mean and variance of the input current are calculated based on multiple input current values, and the mean and variance of the output current are obtained based on multiple output current values.

[0111] The grounding resistance is obtained by using a resistance monitor to detect the grounding device in the photovoltaic inverter;

[0112] The electromagnetic anomaly index is calculated based on the average interference amplitude, mean input current, variance of input current, mean output current, variance of output current, and grounding resistance.

[0113] It should be explained that the raising and alignment of the test antenna of the EMI monitor in the electromagnetic monitoring mechanism means raising the test antenna of the EMI monitor to a preset monitoring height and aligning the receiving direction of the test antenna with the center of gravity of the photovoltaic inverter. The monitoring height is based on the ground and is manually set by the staff of the inverter monitoring center. Preferably, the monitoring height is 3 meters.

[0114] It is understood that the monitoring frequency band is 30MHz to 300MHz. The electromagnetic spectrum curve obtained by monitoring the electromagnetic interference of the photovoltaic inverter based on the preset monitoring frequency band and the preparation monitoring instrument refers to: using the preparation monitoring instrument to monitor the electromagnetic interference signal generated by the photovoltaic inverter within the monitoring frequency band, and generating a frequency-amplitude relationship curve in the preparation monitoring instrument according to the frequency distribution of the electromagnetic interference signal and the amplitude corresponding to each frequency. The curve is the electromagnetic spectrum curve. The technology of using the preparation monitoring instrument to monitor the electromagnetic interference signal generated by the photovoltaic inverter within the monitoring frequency band and generating a frequency-amplitude relationship curve in the preparation monitoring instrument according to the frequency distribution of the electromagnetic interference signal and the amplitude corresponding to each frequency is existing technology and will not be described in detail here.

[0115] For example, if the frequency band spacing is 10MHz, the range of [30MHz, 300MHz] is uniformly divided to obtain multiple frequency ranges: {[30MHz, 40MHz], [40MHz, 50MHz]...[290MHz, 300MHz]}.

[0116] It should be understood that identifying the target spectrum curve based on the frequency range in the electromagnetic spectrum curve means extracting a segment of the electromagnetic spectrum curve that falls within the frequency range to obtain the target spectrum curve. The maximum interference amplitude is the largest amplitude among all amplitudes corresponding to the target spectrum curve.

[0117] For example, if the monitoring interval is 1 second and the monitoring time is 10 seconds, then the current value in the photovoltaic input cable is monitored once every 1 second using a current sensor, and finally 10 current values ​​are obtained, which are the input current values.

[0118] It is understood that the method of monitoring the power distribution output cable in the photovoltaic inverter based on the monitoring interval, monitoring time and the current sensor in the electromagnetic monitoring mechanism to obtain multiple output current values ​​is the same as the method of monitoring the photovoltaic input cable in the photovoltaic inverter based on the monitoring interval, monitoring time and the current sensor in the electromagnetic monitoring mechanism to obtain multiple input current values, and will not be described again here.

[0119] It should be explained that the grounding resistance refers to the resistance of the grounding device, and the techniques for detecting the grounding device in the photovoltaic inverter using a resistance monitor to obtain the grounding resistance, as well as the techniques for monitoring the photovoltaic input cable in the photovoltaic inverter based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism to obtain multiple input current values, are all existing technologies and will not be elaborated here.

[0120] In detail, the formula for calculating the electromagnetic anomaly index is as follows:

[0121]

[0122] Where, ψ B Electromagnetic anomaly index, For the average interference amplitude, and These are the average input current and the average output current, respectively. and These are the preset reference input current value and the preset reference output current value, respectively. and These are the input current variance and the output current variance, respectively, R L Here, e represents the grounding resistance, and e is the natural constant.

[0123] It should be understood that when the average input current deviates from the reference input current value and the average output current deviates from the reference output current value, it indicates that the electrical components in the photovoltaic inverter may have faults such as short circuits or aging. When the variance of the input current and the variance of the output current are larger, it indicates that the fluctuation of multiple input current values ​​and multiple output current values ​​is greater. When the average interference amplitude is larger, that is, when the radiated electromagnetic interference generated by the photovoltaic inverter is greater, it indicates that the electrical components in the photovoltaic inverter may have structural damage, causing high-frequency energy that could have been absorbed or converted to be directly released to the outside in the form of radiation. When the grounding resistance is too large, the external interference current (such as lightning strikes) and the fault current in the photovoltaic inverter cannot be effectively conducted to the ground. Therefore, the electromagnetic anomaly index reflects the degree of abnormality in the electrical performance of the photovoltaic inverter. The larger the electromagnetic anomaly index, the greater the degree of abnormality in the electrical performance of the photovoltaic inverter.

[0124] S4. Use a temperature analysis device to assess the condition of the heat sink and obtain the temperature anomaly weight. Use the temperature analysis device to analyze the temperature image of the semiconductor module and obtain the temperature anomaly index.

[0125] In detail, the process of using a temperature analysis mechanism to assess the condition of the radiator and obtain temperature anomaly weights includes:

[0126] The radiator surface is imaged using a high-definition camera in the temperature analysis unit.

[0127] The pre-constructed initial radiator image and radiator surface image are input into the pre-constructed image comparison model to obtain image similarity.

[0128] The weighting of temperature anomalies is calculated using image similarity, and the formula is shown below:

[0129] ρ T =1-γ s

[0130] Where, ρ T γ is the weight for temperature anomalies. s Image similarity.

[0131] It should be explained that the initial radiator image is an image taken with a high-definition camera when the photovoltaic inverter was first put into use. The radiator surface image refers to an image of the radiator surface taken with a high-definition camera.

[0132] It is understandable that the image comparison model is built on the basis of a convolutional neural network, and the main operating principle of the image comparison model is as follows: first, the convolutional neural network in the image comparison model is used to process the initial radiator image and the radiator surface image through multiple layers of convolution, pooling and activation functions to obtain two feature vectors. Then, the cosine similarity between the two feature vectors is calculated, and the cosine similarity is the image similarity. The above process is a publicly disclosed technical solution, and the embodiments of the present invention will not be described in detail here.

[0133] It should be understood that the smaller the image similarity, the greater the difference between the current state of the heat sink surface and the state of the heat sink surface when the photovoltaic inverter was first put into use. This indicates that the heat sink surface is more severely affected by dust, foreign matter, or surface aging, which in turn leads to a decrease in its heat dissipation performance. Therefore, the temperature anomaly weight reflects the degree of risk of the photovoltaic inverter experiencing temperature anomalies. The greater the temperature anomaly weight, the higher the risk of the photovoltaic inverter experiencing temperature anomalies.

[0134] In detail, the step of using a temperature analysis mechanism to perform temperature image analysis on the semiconductor module to obtain a temperature anomaly index includes:

[0135] Based on the monitoring interval, monitoring time, and temperature analysis mechanism, the infrared camera in the semiconductor module is used to capture multiple infrared temperature images. Each infrared temperature image includes multiple infrared pixels, and each infrared pixel includes an infrared temperature value.

[0136] For each of the multiple infrared temperature images, perform the following operation:

[0137] The average temperature is calculated based on multiple infrared pixels in the infrared temperature image, using the following formula:

[0138]

[0139] in, The average temperature, T i Let be the infrared temperature value of the i-th infrared pixel among multiple infrared pixels, and m be the number of infrared pixels among multiple infrared pixels;

[0140] Perform the following operation on each of the multiple infrared pixels in the infrared temperature image:

[0141] Compare the infrared temperature value corresponding to the infrared pixel with the preset temperature threshold;

[0142] If the infrared temperature value corresponding to an infrared pixel is greater than the temperature threshold, then the infrared pixel is recorded as an over-temperature pixel.

[0143] Summarize the over-temperature pixels to obtain multiple over-temperature pixels, and confirm the number of over-temperature pixels among the multiple over-temperature pixels. The number of over-temperature pixels is the number of over-temperature pixels among the multiple over-temperature pixels.

[0144] The overheat ratio is calculated based on the number of overheats, using the following formula:

[0145]

[0146] Among them, K T The overtemperature ratio, N T The amount of overheating;

[0147] The average temperature and overtemperature ratio corresponding to the infrared temperature images are combined to obtain the infrared data set;

[0148] By summing up the infrared data sets, multiple infrared data sets are obtained.

[0149] The temperature anomaly index is calculated based on multiple infrared data sets, using the following formula:

[0150]

[0151] Where, ψ T This is a temperature anomaly index. K represents the average temperature of the i-th infrared data set among multiple infrared data sets. i T represents the overtemperature ratio of the i-th infrared data group in a set of multiple infrared data groups. y Where L is the temperature threshold, and L is the number of infrared data groups in the multiple infrared data groups.

[0152] For example, if the monitoring interval is 1 second and the monitoring time is 10 seconds, the infrared camera will take a picture of the semiconductor module every 1 second, ultimately obtaining 10 infrared images, which are infrared temperature images. Infrared pixels are the pixels in the infrared temperature images.

[0153] It should be understood that because an infrared camera receives the infrared radiation energy emitted by each point on the semiconductor module through an internal infrared detector array, converts it into an electrical signal and then restores it to a temperature value, thereby generating an infrared temperature image, each infrared pixel in the infrared temperature image corresponds to an infrared temperature value, which reflects the temperature of the corresponding point in reality.

[0154] It should be explained that the temperature threshold is set manually by the staff of the inverter monitoring center. Optionally, the temperature threshold is 90 degrees Celsius.

[0155] For example, if the average temperature is 70°C and the overheat ratio is 0.02, then the infrared data set is: [70°C, 0.02].

[0156] Understandably, the temperature anomaly index reflects the degree of anomaly in the surface temperature of the semiconductor modules in the photovoltaic inverter. The higher the temperature anomaly index, the greater the degree of anomaly in the surface temperature of the semiconductor modules in the photovoltaic inverter.

[0157] S5. Determine the current environmental weights, and use an environmental monitoring agency to monitor the device casing to obtain the operational stability index.

[0158] Specifically, determining the current environmental weights includes:

[0159] Confirm the current wind speed and current rainfall;

[0160] The current environmental weight is calculated using the current wind speed and current rainfall, as shown in the following formula:

[0161]

[0162] Where, ρ E f represents the current environmental weight. d P represents the current wind speed. d This represents the current rainfall.

[0163] It should be explained that the current location refers to the actual location of the photovoltaic inverter.

[0164] For example, at 12:00 on a certain day in history, the precipitation and wind speed at the location of the photovoltaic inverter were obtained from the website of the China Meteorological Administration. The wind speed was 10 mm and the precipitation was 2.5 m / s.

[0165] Understandably, wind and rainfall in the environment can cause mechanical vibration and acoustic interference to the housing of photovoltaic inverters, which in turn affects the stability of measurements taken by environmental monitoring agencies installed on them. Therefore, the current environmental weight reflects the degree of interference of external environmental factors on environmental monitoring agencies. The larger the current environmental weight, the smaller the degree of interference of external environmental factors on environmental monitoring agencies.

[0166] In detail, the monitoring of the device casing by an environmental monitoring agency to obtain an operational stability index includes:

[0167] The sound sensor and vibration sensor in the environmental monitoring agency were used to monitor the device casing to obtain the internal noise intensity and casing vibration amplitude.

[0168] The operational stability index is calculated based on the internal noise intensity and the casing vibration amplitude, using the following formula:

[0169]

[0170] Where, ψ X To maintain operational stability, Su x For internal noise intensity, F k Let ln be the amplitude of the shell vibration, and ln be the natural logarithm.

[0171] It should be explained that internal noise intensity refers to the intensity of noise inside the device housing, while housing vibration amplitude refers to the amplitude of vibration generated by the operation of mechanical parts or external disturbances in the device housing.

[0172] Understandably, the operational stability index reflects the operational stability of the internal components of a photovoltaic inverter; the higher the operational stability index, the greater the operational stability of the internal components of the photovoltaic inverter.

[0173] S6. Input the electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operation stability index into the pre-built multimodal monitoring model to obtain the power distribution anomaly degree.

[0174] In detail, the multimodal monitoring model is as follows:

[0175]

[0176] Among them, Z G For distribution anomaly degree, ρ B For electromagnetic anomaly weights, ρ T For the weight of temperature anomalies, ρ E ψ represents the current environmental weight. T ψ is the temperature anomaly index. X The stability exponent is tanh, where tanh is the hyperbolic tangent function.

[0177] It should be understood that the power distribution anomaly level reflects the degree of abnormality in the overall operating status of the photovoltaic inverter. The greater the power distribution anomaly level, the greater the degree of abnormality in the overall operating status of the photovoltaic inverter.

[0178] S7. Compare the power distribution anomaly degree with the preset anomaly threshold. If the power distribution anomaly degree is greater than or equal to the anomaly threshold, send the pre-built danger signal to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, send the pre-built safety signal to the inverter monitoring terminal to obtain the safety monitoring terminal.

[0179] It should be explained that the inverter monitoring terminal is a pre-programmed software in Python or C++ on the computer of the inverter monitoring center, which can parse the information contained in the danger signal or safety signal and display it on the page of the computer of the inverter monitoring center.

[0180] Understandably, the danger signal is a data packet containing danger information, which is a message used to alert the monitor at the inverter monitoring center that the photovoltaic inverter has malfunctioned. Optionally, the message alerting the monitor at the inverter monitoring center that the photovoltaic inverter has malfunctioned is: "The photovoltaic inverter has malfunctioned and is at risk; please inspect or repair it promptly!" The danger monitoring terminal is the inverter monitoring terminal that receives the danger signal. The safety signal is a data packet containing safety information, which is a message used to inform the monitor at the photovoltaic inverter that the photovoltaic inverter is operating normally. Optionally, the message informing the monitor that the photovoltaic inverter is operating normally is: "The photovoltaic inverter is operating normally." The safety monitoring terminal is the inverter monitoring terminal that receives the safety signal. The anomaly threshold is a value manually set by the monitor at the inverter monitoring center based on historical data. Optionally, the average of multiple distribution anomalies corresponding to multiple photovoltaic inverter failures in the past can be used as the anomaly threshold.

[0181] S8. Complete the power distribution monitoring of the photovoltaic inverter based on the danger monitoring terminal or the safety monitoring terminal.

[0182] For example, when the monitor at the inverter monitoring center sees the message "The photovoltaic inverter has an abnormal risk, please inspect or repair it in time" displayed on the danger monitoring terminal page, they can promptly notify maintenance personnel to repair the photovoltaic inverter. When the monitor at the inverter monitoring center sees the message "The photovoltaic inverter is operating normally" displayed on the safety monitoring terminal page, they can confirm that the current operating status of the photovoltaic inverter is normal and wait for the next time monitoring is required to initiate the power distribution monitoring command again.

[0183] To address the problems described in the background art, this invention receives power distribution monitoring commands and identifies a photovoltaic inverter based on these commands. The photovoltaic inverter includes a device housing, a photovoltaic input cable, a power distribution output cable, a semiconductor module, a grounding device, and a heat sink. It also identifies an electromagnetic monitoring mechanism, a temperature analysis mechanism, and an environmental monitoring mechanism. The electromagnetic monitoring mechanism includes a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The temperature analysis mechanism includes a high-definition camera and an infrared camera. The environmental monitoring mechanism includes a sound sensor and a vibration sensor. The EMI monitor includes a test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing. As can be seen, this embodiment of the invention provides a systematic and automated monitoring environment for photovoltaic inverters by pre-constructing electromagnetic monitoring, temperature analysis, and environmental monitoring mechanisms. It then utilizes a pre-constructed environmental database and electromagnetic monitoring mechanisms to obtain electromagnetic anomaly weights, and uses the electromagnetic monitoring mechanisms to perform electromagnetic analysis on the photovoltaic inverters to obtain an electromagnetic anomaly index. This embodiment of the invention, by combining the environmental database and the monitoring results of the current electromagnetic monitoring mechanisms, performs electromagnetic analysis on the photovoltaic inverters, accurately confirming the degree of electrical performance anomalies and improving the accuracy of photovoltaic inverter monitoring. The temperature analysis mechanism is used to assess the condition of the heat sink and obtain temperature anomaly weights. The temperature analysis mechanism is also used to analyze the semiconductor modules... Temperature image analysis yields a temperature anomaly index. This embodiment of the invention utilizes a temperature analysis mechanism to simultaneously analyze images of the heat sink and semiconductor module, considering both the heat dissipation and heat generation states of the photovoltaic inverter, thus improving the accuracy of photovoltaic inverter monitoring. The current environmental weight is determined, and an environmental monitoring mechanism monitors the device casing to obtain an operational stability index. This embodiment of the invention, by fusing sound and vibration data and combining them with the current environmental conditions, accurately assesses the operational stability of the components within the photovoltaic inverter, improving the accuracy of photovoltaic inverter monitoring. Electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environmental weight, and operational stability index are input into a pre-constructed multimodal monitoring model. In this embodiment of the invention, the power distribution anomaly degree is obtained. It can be seen that the multi-modal monitoring model is used to perform correlation analysis on the electrical performance, temperature rise risk and operational stability of the photovoltaic inverter, thereby improving the accuracy of monitoring the photovoltaic inverter. The power distribution anomaly degree is compared with the preset anomaly threshold. If the power distribution anomaly degree is greater than or equal to the anomaly threshold, a pre-constructed danger signal is sent to the pre-constructed inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, a pre-constructed safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal. Based on the danger monitoring terminal or the safety monitoring terminal, the power distribution monitoring of the photovoltaic inverter is completed. It can be seen that the embodiment of the invention automatically sends danger signals or safety signals to the inverter monitoring terminal through the power distribution anomaly degree, thereby improving the fault response efficiency and the degree of automation of monitoring.Therefore, the present invention can improve the accuracy and automation of monitoring photovoltaic inverters.

[0184] like Figure 2 The diagram shown is a functional block diagram of a multi-mode photovoltaic inverter power distribution monitoring system provided in an embodiment of the present invention.

[0185] The multi-mode photovoltaic inverter power distribution monitoring system 100 described in this invention can be installed in electronic device 1. Depending on the functions implemented, the multi-mode photovoltaic inverter power distribution monitoring system 100 may include a power distribution mechanism confirmation module 101, a mode data analysis module 102, a power distribution status assessment module 103, and a monitoring signal alert module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0186] The power distribution mechanism confirmation module 101 is used to receive power distribution monitoring commands and confirm the photovoltaic inverter based on the power distribution monitoring commands. The photovoltaic inverter includes: a device housing, a photovoltaic input cable, a power distribution output cable, a semiconductor module, a grounding device, and a heat sink. It also confirms the electromagnetic monitoring mechanism, the temperature analysis mechanism, and the environmental monitoring mechanism. The electromagnetic monitoring mechanism includes: a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The temperature analysis mechanism includes: a high-definition camera and an infrared camera. The environmental monitoring mechanism includes: a sound sensor and a vibration sensor. The EMI monitor includes: a test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all installed on the surface of the device housing.

[0187] The modal data analysis module 102 is used to obtain electromagnetic anomaly weights using a pre-built environmental database and an electromagnetic monitoring mechanism, perform electromagnetic analysis on the photovoltaic inverter using the electromagnetic monitoring mechanism to obtain an electromagnetic anomaly index, perform state assessment on the heat sink using a temperature analysis mechanism to obtain a temperature anomaly weight, perform temperature image analysis on the semiconductor module using a temperature analysis mechanism to obtain a temperature anomaly index, confirm the current environmental weight, and monitor the device casing using an environmental monitoring mechanism to obtain an operational stability index.

[0188] The power distribution status assessment module 103 is used to input electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight and operation stability index into a pre-constructed multimodal monitoring model to obtain the power distribution anomaly degree.

[0189] The monitoring signal alert module 104 is used to compare the power distribution anomaly degree with the preset anomaly threshold. If the power distribution anomaly degree is greater than or equal to the anomaly threshold, a pre-constructed danger signal is sent to the pre-constructed inverter monitoring terminal to obtain a danger monitoring terminal. Otherwise, a pre-constructed safety signal is sent to the inverter monitoring terminal to obtain a safety monitoring terminal. Power distribution monitoring of the photovoltaic inverter is completed based on the danger monitoring terminal or the safety monitoring terminal.

[0190] In detail, the modules in the multi-mode photovoltaic inverter power distribution monitoring system 100 described in this embodiment of the invention employ the same methods as described above. Figure 1 The method uses the same technical means as the multi-mode photovoltaic inverter power distribution monitoring method described in the article and can produce the same technical effect, so it will not be repeated here.

[0191] like Figure 3 The diagram shown is a structural schematic of an electronic device 1 for implementing a multi-mode photovoltaic inverter power distribution monitoring method according to an embodiment of the present invention.

[0192] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a multi-mode photovoltaic inverter power distribution monitoring method program.

[0193] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a multi-mode photovoltaic inverter power distribution monitoring method program, but also to temporarily store data that has been output or will be output.

[0194] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a multi-mode photovoltaic inverter power distribution monitoring method program) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0195] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0196] Figure 3 Only electronic devices with components are shown; those skilled in the art will understand that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0197] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0198] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0199] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0200] The multi-mode photovoltaic inverter power distribution monitoring method program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0201] Receive power distribution monitoring instructions and identify the photovoltaic inverter based on the power distribution monitoring instructions. The photovoltaic inverter includes: device housing, photovoltaic input cable, power distribution output cable, semiconductor module, grounding device and heat sink.

[0202] The electromagnetic monitoring mechanism, temperature analysis mechanism, and environmental monitoring mechanism were identified. The electromagnetic monitoring mechanism includes: light sensor, humidity sensor, EMI monitor, current sensor, and resistance monitor. The temperature analysis mechanism includes: high-definition camera and infrared camera. The environmental monitoring mechanism includes: sound sensor and vibration sensor. The EMI monitor includes: test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing.

[0203] Electromagnetic anomaly weights are obtained by using a pre-built environmental database and electromagnetic monitoring institutions. Electromagnetic analysis of photovoltaic inverters is performed by electromagnetic monitoring institutions to obtain electromagnetic anomaly indices.

[0204] The temperature analysis mechanism is used to assess the condition of the heat sink and obtain the temperature anomaly weight. The temperature analysis mechanism is also used to analyze the temperature image of the semiconductor module and obtain the temperature anomaly index.

[0205] The current environmental weights are determined, and the environmental monitoring agency is used to monitor the device casing to obtain the operational stability index.

[0206] The electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operational stability index are input into the pre-built multimodal monitoring model to obtain the power distribution anomaly degree.

[0207] Compare the power distribution anomaly level with the preset anomaly threshold. If the power distribution anomaly level is greater than or equal to the anomaly threshold, the pre-built danger signal is sent to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, the pre-built safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal.

[0208] Power distribution monitoring of photovoltaic inverters is completed based on hazard monitoring terminals or safety monitoring terminals.

[0209] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0210] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0211] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0212] Receive power distribution monitoring instructions and identify the photovoltaic inverter based on the power distribution monitoring instructions. The photovoltaic inverter includes: device housing, photovoltaic input cable, power distribution output cable, semiconductor module, grounding device and heat sink.

[0213] The electromagnetic monitoring mechanism, temperature analysis mechanism, and environmental monitoring mechanism were identified. The electromagnetic monitoring mechanism includes: light sensor, humidity sensor, EMI monitor, current sensor, and resistance monitor. The temperature analysis mechanism includes: high-definition camera and infrared camera. The environmental monitoring mechanism includes: sound sensor and vibration sensor. The EMI monitor includes: test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing.

[0214] Electromagnetic anomaly weights are obtained by using a pre-built environmental database and electromagnetic monitoring institutions. Electromagnetic analysis of photovoltaic inverters is performed by electromagnetic monitoring institutions to obtain electromagnetic anomaly indices.

[0215] The temperature analysis mechanism is used to assess the condition of the heat sink and obtain the temperature anomaly weight. The temperature analysis mechanism is also used to analyze the temperature image of the semiconductor module and obtain the temperature anomaly index.

[0216] The current environmental weights are determined, and the environmental monitoring agency is used to monitor the device casing to obtain the operational stability index.

[0217] The electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operational stability index are input into the pre-built multimodal monitoring model to obtain the power distribution anomaly degree.

[0218] Compare the power distribution anomaly level with the preset anomaly threshold. If the power distribution anomaly level is greater than or equal to the anomaly threshold, the pre-built danger signal is sent to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, the pre-built safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal.

[0219] Power distribution monitoring of photovoltaic inverters is completed based on hazard monitoring terminals or safety monitoring terminals.

[0220] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0221] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0222] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0223] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0224] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring the power distribution of a photovoltaic inverter based on multi-mode operation, characterized in that, The method includes: Receive power distribution monitoring instructions and identify the photovoltaic inverter based on the power distribution monitoring instructions. The photovoltaic inverter includes: device housing, photovoltaic input cable, power distribution output cable, semiconductor module, grounding device and heat sink. The electromagnetic monitoring mechanism, temperature analysis mechanism, and environmental monitoring mechanism were identified. The electromagnetic monitoring mechanism includes: light sensor, humidity sensor, EMI monitor, current sensor, and resistance monitor. The temperature analysis mechanism includes: high-definition camera and infrared camera. The environmental monitoring mechanism includes: sound sensor and vibration sensor. The EMI monitor includes: test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing. Electromagnetic anomaly weights are obtained by using a pre-built environmental database and electromagnetic monitoring institutions. Electromagnetic analysis of photovoltaic inverters is performed by electromagnetic monitoring institutions to obtain electromagnetic anomaly indices. The temperature analysis mechanism is used to assess the condition of the heat sink and obtain the temperature anomaly weight. The temperature analysis mechanism is also used to analyze the temperature image of the semiconductor module and obtain the temperature anomaly index. The current environmental weights are determined, and the environmental monitoring agency is used to monitor the device casing to obtain the operational stability index. The electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operational stability index are input into the pre-built multimodal monitoring model to obtain the power distribution anomaly degree. Compare the power distribution anomaly level with the preset anomaly threshold. If the power distribution anomaly level is greater than or equal to the anomaly threshold, the pre-built danger signal is sent to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, the pre-built safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal. Power distribution monitoring of photovoltaic inverters is completed based on hazard monitoring terminals or safety monitoring terminals.

2. The photovoltaic inverter power distribution monitoring method based on multi-mode as described in claim 1, characterized in that, The method of obtaining electromagnetic anomaly weights using a pre-built environmental database and electromagnetic monitoring institutions includes: The current time is determined, and the current time range is determined based on the current time and the preset reference duration; Based on the current time range, multiple historical moment data are extracted from the environmental database. The historical moment data includes: historical light intensity and historical humidity. Multiple historical light intensities and multiple historical humidity values ​​are extracted from data from multiple historical moments. The current reference light intensity is calculated based on the multiple historical light intensities, where the current reference light intensity is the average of the multiple historical light intensities. Calculate the current reference humidity based on multiple historical humidity levels; Based on preset monitoring intervals, preset monitoring times, and light and humidity sensors, multiple current light intensities and multiple current humidity levels are obtained. The electromagnetic anomaly weight is calculated based on multiple current light intensities, multiple current humidity levels, current reference light intensity, and current reference humidity.

3. The photovoltaic inverter power distribution monitoring method based on multi-mode as described in claim 2, characterized in that, The electromagnetic analysis of the photovoltaic inverter using an electromagnetic monitoring mechanism to obtain an electromagnetic anomaly index includes: The test antenna of the EMI monitor in the electromagnetic monitoring mechanism is raised and aligned to prepare the monitor; Electromagnetic interference monitoring of photovoltaic inverters is performed based on preset monitoring frequency bands and prepared monitoring instruments to obtain electromagnetic spectrum curves, where the horizontal axis of the electromagnetic spectrum curve is frequency and the vertical axis of the electromagnetic spectrum curve is amplitude. The monitoring frequency band is uniformly divided based on a preset frequency band interval to obtain multiple frequency ranges; Perform the following operation for each of the multiple frequency ranges: Based on the frequency range, the target spectrum curve is identified in the electromagnetic spectrum curve, and the maximum interference amplitude of the target spectrum curve is determined. The maximum interference amplitude is summarized to obtain multiple maximum interference amplitudes. The average interference amplitude is calculated based on the multiple maximum interference amplitudes. Based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism, the photovoltaic input cable in the photovoltaic inverter is monitored to obtain multiple input current values; Based on the monitoring interval, monitoring time, and current sensor in the electromagnetic monitoring mechanism, the power distribution output cable in the photovoltaic inverter is monitored to obtain multiple output current values; The mean and variance of the input current are calculated based on multiple input current values, and the mean and variance of the output current are obtained based on multiple output current values. The grounding resistance is obtained by using a resistance monitor to detect the grounding device in the photovoltaic inverter; The electromagnetic anomaly index is calculated based on the average interference amplitude, mean input current, variance of input current, mean output current, variance of output current, and grounding resistance.

4. The photovoltaic inverter power distribution monitoring method based on multi-mode as described in claim 3, characterized in that, The formula for calculating the electromagnetic anomaly index is as follows: Where, ψ B Electromagnetic anomaly index, For the average interference amplitude, and These are the average input current and the average output current, respectively. and These are the preset reference input current value and the preset reference output current value, respectively. and These are the input current variance and the output current variance, respectively, R L Here, e represents the grounding resistance, and e is the natural constant.

5. The photovoltaic inverter power distribution monitoring method based on multi-mode as described in claim 4, characterized in that, The process of using a temperature analysis mechanism to assess the condition of the radiator and obtain temperature anomaly weights includes: The radiator surface is imaged using a high-definition camera in the temperature analysis unit. The pre-constructed initial radiator image and radiator surface image are input into the pre-constructed image comparison model to obtain image similarity. Calculate temperature anomaly weights using image similarity.

6. The photovoltaic inverter power distribution monitoring method based on multi-mode as described in claim 5, characterized in that, The process of using a temperature analysis mechanism to analyze the temperature image of the semiconductor module and obtain a temperature anomaly index includes: Based on the monitoring interval, monitoring time, and temperature analysis mechanism, the infrared camera in the semiconductor module is used to capture multiple infrared temperature images. Each infrared temperature image includes multiple infrared pixels, and each infrared pixel includes an infrared temperature value. For each of the multiple infrared temperature images, perform the following operation: Calculate the average temperature based on multiple infrared pixels in the infrared temperature image; Perform the following operation on each of the multiple infrared pixels in the infrared temperature image: Compare the infrared temperature value corresponding to the infrared pixel with the preset temperature threshold; If the infrared temperature value corresponding to an infrared pixel is greater than the temperature threshold, then the infrared pixel is recorded as an over-temperature pixel. Summarize the over-temperature pixels to obtain multiple over-temperature pixels, and confirm the number of over-temperature pixels among the multiple over-temperature pixels. The number of over-temperature pixels is the number of over-temperature pixels among the multiple over-temperature pixels. Calculate the overheat ratio based on the number of overheats; The average temperature and overtemperature ratio corresponding to the infrared temperature images are combined to obtain the infrared data set; By summing up the infrared data sets, multiple infrared data sets are obtained. The temperature anomaly index was calculated based on multiple infrared data sets.

7. The photovoltaic inverter power distribution monitoring method based on multimode as described in claim 6, characterized in that, The determination of the current environmental weight includes: Confirm the current wind speed and current rainfall; Calculate the current environmental weight using the current wind speed and current rainfall.

8. The photovoltaic inverter power distribution monitoring method based on multi-mode as described in claim 7, characterized in that, The method of using an environmental monitoring agency to monitor the device casing and obtain an operational stability index includes: The sound sensor and vibration sensor in the environmental monitoring agency were used to monitor the device casing to obtain the internal noise intensity and casing vibration amplitude. The operational stability index is calculated based on the internal noise intensity and the vibration amplitude of the casing.

9. The photovoltaic inverter power distribution monitoring method based on multimode as described in claim 8, characterized in that, The multimodal monitoring model is shown below: Among them, Z G For distribution anomaly degree, ρ B For electromagnetic anomaly weights, ρ T For the weight of temperature anomalies, ρ E ψ represents the current environmental weight. T ψ is the temperature anomaly index. X The stability exponent is tanh, where tanh is the hyperbolic tangent function.

10. A multi-mode photovoltaic inverter power distribution monitoring system, characterized in that, The system includes: The power distribution mechanism confirmation module is used to receive power distribution monitoring commands and confirm the photovoltaic inverter based on the commands. The photovoltaic inverter includes: a device housing, a photovoltaic input cable, a power distribution output cable, a semiconductor module, a grounding device, and a heat sink. The module also confirms the electromagnetic monitoring mechanism, the temperature analysis mechanism, and the environmental monitoring mechanism. The electromagnetic monitoring mechanism includes: a light sensor, a humidity sensor, an EMI monitor, a current sensor, and a resistance monitor. The temperature analysis mechanism includes: a high-definition camera and an infrared camera. The environmental monitoring mechanism includes: a sound sensor and a vibration sensor. The EMI monitor includes: a test antenna. The light sensor, humidity sensor, sound sensor, and vibration sensor are all mounted on the surface of the device housing. The modal data analysis module is used to obtain electromagnetic anomaly weights using a pre-built environmental database and electromagnetic monitoring mechanism, perform electromagnetic analysis on the photovoltaic inverter using the electromagnetic monitoring mechanism to obtain the electromagnetic anomaly index, perform state assessment on the heat sink using the temperature analysis mechanism to obtain the temperature anomaly weights, perform temperature image analysis on the semiconductor module using the temperature analysis mechanism to obtain the temperature anomaly index, confirm the current environmental weights, and monitor the device casing using the environmental monitoring mechanism to obtain the operating stability index. The power distribution status assessment module is used to input electromagnetic anomaly weight, electromagnetic anomaly index, temperature anomaly weight, temperature anomaly index, current environment weight, and operation stability index into a pre-built multimodal monitoring model to obtain the power distribution anomaly degree. The monitoring signal alert module is used to compare the power distribution anomaly degree with the preset anomaly threshold. If the power distribution anomaly degree is greater than or equal to the anomaly threshold, a pre-built danger signal is sent to the pre-built inverter monitoring terminal to obtain the danger monitoring terminal. Otherwise, a pre-built safety signal is sent to the inverter monitoring terminal to obtain the safety monitoring terminal. Based on the danger monitoring terminal or the safety monitoring terminal, the power distribution monitoring of the photovoltaic inverter is completed.

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