Method and system for carrier transmission data of real-time monitoring system of photovoltaic power station

Abstract

The invention relates to the technical field of photovoltaic power station data transmission, and discloses a method and a system for carrier transmission data of a real-time monitoring system of a photovoltaic power station. The carrier wave data transmission method specifically comprises the following steps: S101, deploying a sensor network on key equipment of a photovoltaic module, an inverter, a combiner box and a transformer of a photovoltaic power station, collecting equipment operation state data in real time, and quantizing an analog signal into a 16-bit-precision digital signal through an ADC (Analog to Digital Converter); and S102, packaging the quantized 16-bit precision digital signal into a data frame, adding a device ID, a timestamp and a CRC check code to the head of the data frame, and loading a power line through carrier communication. The optimized OFDM modulation 512 subcarrier / 1-30 MHz frequency band and pi-type filtering coupling design guarantees communication reliability, stable transmission can still be achieved even in a strong electromagnetic interference environment, the false alarm rate is effectively reduced by more than 40% through a dynamic threshold mechanism, and crossing from passive response to predictive maintenance is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power station data transmission, and in particular to a method and system for carrier wave data transmission in a real-time monitoring system of a photovoltaic power station. Background Art

[0002] With the large-scale application of photovoltaic power stations, real-time monitoring of equipment operating status has become crucial to ensure stable operation of power stations and improve power generation efficiency.

[0003] Traditional monitoring methods mainly rely on manual patrols and regular inspections, which have problems such as low efficiency and inability to achieve real-time monitoring. In recent years, although wireless communication and wired communication technologies have been applied, they have shortcomings such as complex wiring, high cost, and susceptibility to environmental interference.

[0004] Therefore, there is an urgent need to design a method and system that can monitor the operating status of photovoltaic power station equipment in real time and accurately, and is low-cost, highly reliable, and easy to integrate. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for carrier data transmission in a real-time monitoring system for photovoltaic power plants. This method uses carrier communication technology to achieve millisecond-level real-time monitoring of the equipment's operating status. By combining a multi-dimensional sensor network, such as temperature / current / vibration, with fusion analysis of environmental parameters such as light and humidity, the accuracy of fault identification is significantly improved. Furthermore, the optimized OFDM modulation with 512 subcarriers / 1-30MHz frequency band and π-type filter coupling design ensures communication reliability, aiming to address the problems in the prior art.

[0006] The present invention is implemented as follows: a method for carrier wave data transmission in a real-time monitoring system for a photovoltaic power station, specifically comprising the following steps: S101: Deploy sensor networks on key equipment in a PV power plant, including PV panels, inverters, combiner boxes, and transformers, to collect real-time data on equipment operating status. The analog signals are converted into digital signals with 16-bit precision using ADC converters. S102: Encapsulate the quantized 16-bit precision digital signal into a data frame, add the device ID, timestamp and CRC checksum to the data frame header, load it onto the power line through carrier communication, and inject it into the power line through the coupling capacitor for transmission to the monitoring center; S103: The monitoring center verifies and analyzes the received data frames, removes transient noise, removes outliers using the Laida criterion, and simultaneously calculates and extracts the time-frequency domain features of the data frames. The features are then input into a pre-trained LSTM-Attention hybrid model to output a device status scoring standard. S104: The monitoring center dynamically adjusts the abnormality threshold based on the device type and environmental parameters. If the score exceeds the threshold, it is considered abnormal and generates an alarm information package. The alarm information package contains the device ID, GPS coordinates, abnormality type code, score deviation value and timestamp, realizing the triggering of a multi-level alarm mechanism; S105: Alarm information is pushed to the operation and maintenance terminal via the MQTT protocol. The operation and maintenance terminal displays the 3D topology of the equipment and locates the abnormal point. A work order is generated simultaneously and assigned to the nearest operation and maintenance personnel. After the maintenance is completed, the operation and maintenance personnel feedback the processing results to the monitoring center. The monitoring center updates the equipment health file and feedbacks to the multi-level alarm mechanism to stop the alarm.

[0007] Furthermore, in S101, a sensor network is deployed on key equipment such as photovoltaic modules, inverters, combiner boxes, and transformers in the photovoltaic power station to collect equipment operating status data in real time, including: The sensor network deployment includes: deploying thin-film temperature sensors on the backplane of photovoltaic modules, installing PT100 platinum resistors on the inverter heat sink, integrating Hall-effect closed-loop current sensors on the combiner box bus, and fixing MEMS vibration sensors on the transformer body. The sensor network covers the head and tail nodes of each module string, the inverter IGBT module, and the transformer winding core. The operating status data of the photovoltaic modules, inverters, combiner boxes and transformers of the photovoltaic power station include physical quantity data of temperature, current, voltage, power and vibration parameters, and the sampling frequency of the status data is not less than 10 Hz.

[0008] Furthermore, in S102, the quantized 16-bit precision digital signal is encapsulated into a data frame, and the device ID, timestamp and CRC check code are added to the data frame header, including: Orthogonal frequency division multiplexing (OFDM) modulation is used to divide the 1–30 MHz frequency band into 512 subcarriers. A cyclic prefix is ​​used to eliminate multipath interference. The frame header contains the device ID, high-precision timestamp, and transmission sequence number. The data area is divided into independent fields for temperature, current, and voltage parameters. A double CRC checksum is appended to the end of the frame. The frame length is fixed at 256 bytes, and the insufficient part is padded with random numbers to ensure the bandwidth utilization during power line transmission; Subcarriers are allocated at equal intervals in the 1-30MHz frequency band with a subcarrier spacing of 58.6kHz. A cyclic prefix is ​​inserted to suppress the multipath effect, and the modulated signal is injected into the power line through a π-type filter coupling circuit.

[0009] Furthermore, subcarriers are allocated at equal intervals in the 1-30 MHz frequency band with a subcarrier spacing of 58.6 kHz. A cyclic prefix is ​​inserted to suppress the multipath effect. The modulated signal is injected into the power line through a π-type filter coupling circuit, including: The 1-30 MHz frequency band is divided into 512 equally spaced subcarriers, with guard bands reserved at both ends to avoid grid harmonic interference. Each subcarrier is modulated using QPSK, and a time-domain signal is generated through IFFT transform. A cyclic prefix is ​​inserted to cover the maximum multipath delay of the power line. Subcarrier power is dynamically allocated based on channel detection results. The optimized π-type filter coupling circuit, while meeting the requirements of 1-30MHz passband, less than 0.8dB insertion loss and 2kV high-voltage isolation, combines GDT surge protection with Smith chart impedance matching to efficiently inject the modulated signal into the combiner box DC bus.

[0010] Furthermore, in S103, the monitoring center verifies and analyzes the received data frame, removes transient noise, removes outliers in combination with the Laida criterion, and simultaneously calculates and extracts the time-frequency domain features of the data frame, which are then input into the pre-trained LSTM-Attention hybrid model, including: The monitoring center verifies and analyzes the received data frames and performs three-level processing: Data cleaning: Use sliding window filtering to remove transient noise and outliers. The window size must be more than 50 samples. Feature extraction, calculation of time-frequency domain features of current harmonic distortion rate, temperature gradient change rate, and vibration spectrum entropy; Anomaly detection is based on extracting calculated time-frequency domain features, inputting them into a pre-trained LSTM-Attention hybrid model for identification and judgment, and outputting a device status score. If the score exceeds a threshold, an anomaly is determined.

[0011] Furthermore, in S104, the monitoring center dynamically adjusts the abnormality threshold according to the device type and environmental parameters. If the score exceeds the threshold, it is determined to be abnormal and an alarm information package is generated, including: The basic threshold is preset based on the device type and dynamically modified in combination with real-time environmental parameters. The temperature threshold is calculated according to the formula: Tadj=Tbase+k1·GHI-k2·RH; Where GHI is light intensity, RH is humidity, k1 = 0.02°C·m² / Wk, and k2 = 0.5°C / %. The vibration threshold is dynamically generated by linking wind speed data with a Weibull distribution model. The threshold is refreshed within a preset time and the device status score is verified to be exceeded. When the status score exceeds the dynamic threshold, a binary alarm package is automatically generated. The alarm package triggers a three-level alarm based on the deviation value. The first alarm is pushed immediately, and the continuous abnormality is pushed to 2 n Retransmit at intervals of seconds, where n is the number of cycles during which the anomaly persists.

[0012] Furthermore, when the status score exceeds the dynamic threshold, a binary alarm package is automatically generated. The alarm package triggers three levels of alarms based on the deviation value, including: Automatic grading is performed based on the obtained score deviation value ΔS = |actual score - dynamic threshold| / threshold. When ΔS is less than 20%, a level 1 alarm is triggered, which sends a text message to the operation and maintenance team leader. 20%≤ΔS<50% triggers a level 2 alarm, which is reported to the responsible team via an app pop-up window and voice broadcast. ΔS≥50% or involves core equipment triggers a level 3 alarm, which triggers an emergency shutdown protection of the SCADA system and is simultaneously pushed to the large screen of the power plant control center. The first-level alarm sends the device ID + abnormal code through the operator's SMS gateway. The second-level alarm is pushed to the mobile terminal via the MQTT protocol, triggering a strong vibration reminder. The third-level alarm uses hard wiring + ModbusTCP dual channels to transmit to SCADA and execute the preset protection logic. All alarm logs are stored in the blockchain evidence library in real time and can be traced.

[0013] Furthermore, in S105, after the maintenance is completed, the operation and maintenance personnel feedback the processing results to the monitoring center. The monitoring center updates the equipment health file and feedbacks to the multi-level alarm mechanism to stop the alarm, including: Operation and maintenance personnel use a mobile terminal app to scan the device's QR code and submit a maintenance report, including the cause of the fault, treatment measures, replacement part serial number, and processing time. After automatically verifying the data integrity, it is encrypted and transmitted to the monitoring center, triggering the electronic work order closed-loop process and simultaneously terminating the device's alarm status. The monitoring center analyzes fault handling records provided by operations and maintenance personnel, automatically calculates the mean-to-tr (MTTR) and fault level, and activates a threshold adaptive mechanism. Based on the historical number of faults and the temperature distribution curve, the center lowers the baseline temperature threshold using a step-by-step algorithm. Effective features are simultaneously extracted as input to the predictive maintenance model, generating a unique health baseline for the equipment. The updated health index is synchronized to the alarm module, SCADA system and mobile terminal in real time. When the health index is lower than the preset safety value, a preventive maintenance work order is automatically generated and assigned to the responsible person according to the team load balancing algorithm, and a spare parts inventory warning is triggered simultaneously.

[0014] Compared with the prior art, the method and system for carrier wave data transmission in a real-time monitoring system for a photovoltaic power station provided by the present invention have the following beneficial effects: 1. Carrier communication technology enables millisecond-level real-time monitoring of equipment operating status. Combined with a multi-dimensional sensor network, such as temperature, current, and vibration, and integrated analysis of environmental parameters such as light and humidity significantly improves fault identification accuracy. Optimized OFDM modulation with 512 subcarriers / 1-30MHz frequency band and π-type filter coupling ensures communication reliability, enabling stable transmission even in strong electromagnetic interference environments. A dynamic threshold mechanism effectively reduces false alarm rates by over 40%, enabling a transition from passive response to predictive maintenance. 2. Data is transmitted using the existing power lines of the photovoltaic power station, saving the cost of dedicated communication wiring. The modular architecture supports seamless expansion from distributed household power stations to 100-megawatt power stations. The closed-loop operation and maintenance system shortens the average fault repair time and reduces power generation losses. The combination of the three-level alarm mechanism and blockchain evidence storage not only meets the requirements of security and compliance audits, but also extends the life of equipment through preventive maintenance, thereby comprehensively reducing the operation and maintenance costs of the power station throughout its life cycle.

[0015] A system for transmitting data via a carrier wave in a real-time monitoring system for a photovoltaic power station, for executing the above-mentioned method for transmitting data via a carrier wave in a real-time monitoring system, comprising: The data acquisition module is deployed on key equipment such as photovoltaic panels, inverters, combiner boxes, and transformers. It is used to collect equipment operating status data in real time and quantize analog signals into 16-bit digital signals through the built-in ADC converter. The carrier communication module is connected to the data acquisition module and is used to encapsulate the quantized digital signal into a data frame, add the device ID, timestamp and CRC check code to the frame header, load it into the power line through orthogonal frequency division multiplexing modulation technology, and inject it into the power line through the coupling capacitor for transmission to the monitoring center; The intelligent analysis module, located in the monitoring center, verifies and analyzes received data frames, performs noise removal and outlier removal, and simultaneously calculates time-frequency domain features such as current harmonic distortion and vibration spectrum entropy. It then inputs the pre-trained LSTM-Attention hybrid model to output a device status score. The dynamic alarm module, connected to the intelligent analysis module, is used to dynamically adjust the anomaly threshold based on the device type and environmental parameters. When the score exceeds the threshold, an alarm information package containing the device ID, GPS coordinates, anomaly type code, score deviation value and timestamp is generated, triggering a multi-level alarm mechanism; The closed-loop operation and maintenance module is used to push alarm information to the operation and maintenance terminal through the MQTT protocol, locate abnormal points in the terminal's three-dimensional topology map, automatically generate work orders, and assign them to the nearest operation and maintenance personnel. After receiving feedback on maintenance completion, the device health file is updated and the alarm status is terminated.

[0016] Specifically, the carrier communication module includes: The signal encapsulation unit is used to encapsulate the 16-bit digital signal into a data frame with a fixed length of 256 bytes. The device ID and μs-level timestamp are written into the frame header, and a double CRC check code is appended to the frame tail. The anti-interference transmission unit adopts 512-subcarrier OFDM modulation technology, inserts a cyclic prefix to suppress multipath effects, and injects it into the combiner box DC bus through a π-type filter coupling circuit; Signal enhancement unit, deploying gain-adjustable relay amplifiers at power line branch nodes, combining DPSK modulation with forward error correction coding to control the bit error rate to 10 -9 the following. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic flow chart of a method for carrier wave data transmission in a real-time monitoring system for a photovoltaic power station proposed by the present invention; Figure 2 This is a schematic block diagram of the process of deploying a sensor network on key equipment such as photovoltaic modules, inverters, combiner boxes, and transformers in a photovoltaic power station to collect equipment operating status data in real time in a method for carrier transmission of data in a real-time monitoring system of a photovoltaic power station proposed by the present invention; Figure 3 This is a structural diagram of a system for carrier wave data transmission in a real-time monitoring system of a photovoltaic power station proposed by the present invention; Figure 4 This is a structural diagram of a carrier communication module in a system for carrier transmission of data in a real-time monitoring system for a photovoltaic power station proposed by the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] The implementation of the present invention is described in detail below with reference to specific embodiments.

[0020] The same or similar numbers in the drawings of this embodiment correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "up", "down", "left", "right", etc. indicate directions or positional relationships, they are based on the directions or positional relationships shown in the drawings. This is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0021] Reference Figure 1-2 As shown, a method for carrier wave data transmission in a real-time monitoring system of a photovoltaic power station specifically includes the following steps: S101: Deploy sensor networks on key equipment in a PV power plant, including PV panels, inverters, combiner boxes, and transformers, to collect real-time data on equipment operating status. The analog signals are converted into digital signals with 16-bit precision using ADC converters. Among them, sensor networks are deployed on key equipment such as photovoltaic modules, inverters, combiner boxes, and transformers in photovoltaic power stations to collect real-time equipment operating status data, including: The sensor network deployment includes: thin-film temperature sensors deployed on the backplane of photovoltaic modules, PT100 platinum resistors installed on the inverter heat sink, Hall-effect closed-loop current sensors integrated into the combiner box bus, MEMS vibration sensors fixed to the transformer body, and full coverage of the first and last nodes of each module string, the inverter IGBT module, and the transformer winding core. The operating status data of key equipment such as photovoltaic modules, inverters, combiner boxes and transformers in photovoltaic power stations shall include physical quantity data of temperature, current, voltage, power and vibration parameters. The sampling frequency of status data shall be no less than 10 Hz. S102: Encapsulate the quantized 16-bit precision digital signal into a data frame, add the device ID, timestamp and CRC checksum to the data frame header, load it onto the power line through carrier communication, and inject it into the power line through the coupling capacitor for transmission to the monitoring center; The quantized 16-bit precision digital signal is encapsulated into a data frame, and the data frame header is added with a device ID, timestamp, and CRC checksum, including: Orthogonal frequency division multiplexing (OFDM) modulation is used to divide the 1–30 MHz frequency band into 512 subcarriers. A cyclic prefix is ​​used to eliminate multipath interference. The frame header contains the device ID, high-precision timestamp, and transmission sequence number. The data area is divided into independent fields for temperature, current, and voltage parameters. A double CRC checksum is appended to the end of the frame. The frame length is fixed at 256 bytes, and the insufficient part is padded with random numbers to ensure the bandwidth utilization during power line transmission; Subcarriers are allocated at equal intervals in the 1-30MHz frequency band, with a subcarrier spacing of 58.6kHz. Cyclic prefixes are inserted to suppress multipath effects, and the modulated signal is injected into the power line through a π-type filter coupling circuit. S103: The monitoring center verifies and analyzes the received data frames, removes transient noise, removes outliers using the Laida criterion, and simultaneously calculates and extracts the time-frequency domain features of the data frames. The features are then input into a pre-trained LSTM-Attention hybrid model to output a device status scoring standard. The monitoring center verifies and analyzes the received data frames, removes transient noise, removes outliers using the Laida criterion, and simultaneously calculates and extracts the time-frequency domain features of the data frames. The features are then fed into a pre-trained LSTM-Attention hybrid model, including: The monitoring center verifies and analyzes the received data frames and performs three-level processing: Data cleaning: Use sliding window filtering to remove transient noise and outliers. The window size should be more than 50 samples. Feature extraction, calculation of time-frequency domain features of current harmonic distortion rate, temperature gradient change rate, and vibration spectrum entropy; Anomaly detection is based on extracting calculated time-frequency domain features, inputting them into a pre-trained LSTM-Attention hybrid model for identification and judgment, and outputting a device status score. If the score exceeds a threshold, an anomaly is determined. S104: The monitoring center dynamically adjusts the abnormality threshold based on the device type and environmental parameters. If the score exceeds the threshold, it is considered abnormal and generates an alarm information package. The alarm information package contains the device ID, GPS coordinates, abnormality type code, score deviation value and timestamp, realizing the triggering of a multi-level alarm mechanism; The monitoring center dynamically adjusts the abnormality threshold based on the device type and environmental parameters. If the score exceeds the threshold, it is considered abnormal and an alarm information package is generated, including: The basic threshold is preset based on the device type and dynamically corrected in combination with real-time environmental parameters. The temperature threshold is calculated according to the formula: Tadj=Tbase+k1·GHI-k2·RH; Where GHI is light intensity, RH is humidity, k1 = 0.02°C·m² / Wk, and k2 = 0.5°C / %. The vibration threshold is dynamically generated by linking wind speed data with a Weibull distribution model. The threshold is refreshed within a preset time and the device status score is verified to be exceeded. When the status score exceeds the dynamic threshold, a binary alarm package is automatically generated. The alarm package triggers a three-level alarm based on the deviation value. The first alarm is pushed immediately, and the continuous abnormality is pushed to 2 n Retransmission interval is 1 second, where n is the number of cycles during which the abnormality persists; S105: Alarm information is pushed to the operation and maintenance terminal via the MQTT protocol. The terminal displays a three-dimensional topology map of the equipment and locates abnormal points. A work order is simultaneously generated and assigned to the nearest operation and maintenance personnel. After maintenance is completed, the operation and maintenance personnel feedback the processing results to the monitoring center. The monitoring center updates the equipment health record and feedback is sent to the multi-level alarm mechanism to stop the alarm. Carrier communication technology is used to achieve millisecond-level real-time monitoring of the equipment's operating status. Combined with a multi-dimensional sensor network, such as temperature, current, vibration, and other environmental parameters such as light and humidity, the accuracy of fault identification is significantly improved. At the same time, the optimized OFDM modulation 512 subcarriers / 1-30MHz frequency band and π-type filter coupling design ensure communication reliability. Stable transmission is still possible even in strong electromagnetic interference environments. The dynamic threshold mechanism effectively reduces the false alarm rate by more than 40%, achieving a leap from passive response to predictive maintenance.

[0022] In S102 of this embodiment, subcarriers are allocated at equal intervals in the 1-30 MHz frequency band, with a subcarrier interval of 58.6 kHz. A cyclic prefix is ​​inserted to suppress multipath effects, and a modulated signal is injected into the power line through a π-type filter coupling circuit, including: The 1-30 MHz frequency band is divided into 512 equally spaced subcarriers, with guard bands reserved at both ends to avoid grid harmonic interference. Each subcarrier is modulated using QPSK, and a time-domain signal is generated through IFFT transform. A cyclic prefix is ​​inserted to cover the maximum multipath delay of the power line. Subcarrier power is dynamically allocated based on channel detection results. The optimized π-type filter coupling circuit, while meeting the requirements of 1-30MHz passband, less than 0.8dB insertion loss and 2kV high-voltage isolation, combines GDT surge protection with Smith chart impedance matching to efficiently inject the modulated signal into the combiner box DC bus.

[0023] In S104 of this embodiment, when the status score exceeds the dynamic threshold, a binary alarm package is automatically generated. The alarm package triggers three levels of alarms based on the deviation value, including: Automatic grading is performed based on the obtained score deviation value ΔS = |actual score - dynamic threshold| / threshold. When ΔS is less than 20%, a level 1 alarm is triggered, which sends a text message to the operation and maintenance team leader. 20%≤ΔS<50% triggers a level 2 alarm, which is reported to the responsible team via an app pop-up window and voice broadcast. ΔS≥50% or involves core equipment triggers a level 3 alarm, which triggers an emergency shutdown protection of the SCADA system and is simultaneously pushed to the large screen of the power plant control center. The first-level alarm sends the device ID + abnormal code through the operator's SMS gateway. The second-level alarm is pushed to the mobile terminal via the MQTT protocol, triggering a strong vibration reminder. The third-level alarm uses hard wiring + ModbusTCP dual channels to transmit to SCADA and execute the preset protection logic. All alarm logs are stored in the blockchain evidence library in real time and can be traced.

[0024] In S105 of this embodiment, after the maintenance is completed, the operation and maintenance personnel feedback the processing results to the monitoring center. The monitoring center updates the equipment health file and feedbacks to the multi-level alarm mechanism to stop the alarm, including: Operation and maintenance personnel use a mobile terminal app to scan the device's QR code and submit a maintenance report, including the cause of the fault, treatment measures, replacement part serial number, and processing time. After automatically verifying the data integrity, it is encrypted and transmitted to the monitoring center, triggering the electronic work order closed-loop process and simultaneously terminating the device's alarm status. The monitoring center analyzes fault handling records provided by operations and maintenance personnel, automatically calculates the mean-to-tr (MTTR) and fault level, and activates a threshold adaptive mechanism. Based on the historical number of faults and the temperature distribution curve, the center lowers the baseline temperature threshold using a step-by-step algorithm. Effective features are simultaneously extracted as input to the predictive maintenance model, generating a unique health baseline for the equipment. The updated health index is synchronized to the alarm module, SCADA system and mobile terminal in real time. When the health index is lower than the preset safety value, a preventive maintenance work order is automatically generated and assigned to the responsible person according to the team load balancing algorithm, and a spare parts inventory warning is triggered simultaneously.

[0025] This technical solution uses the existing power lines of photovoltaic power stations to transmit data, saving the cost of dedicated communication wiring. The modular architecture supports seamless expansion from distributed household power stations to 100-megawatt power stations. The closed-loop operation and maintenance system shortens the average fault repair time and reduces power generation losses. The combination of a three-level alarm mechanism and blockchain evidence storage not only meets security and compliance audit requirements, but also extends equipment life through preventive maintenance, comprehensively reducing the operation and maintenance costs of the power station throughout its life cycle.

[0026] Reference Figure 3-4As shown, a system for carrier transmission data of a real-time monitoring system of a photovoltaic power station is used to execute the above-mentioned method for carrier transmission data of a real-time monitoring system. The system includes: a data acquisition module, which is deployed on photovoltaic components, inverters, junction boxes and transformer key equipment, and is used to collect equipment operation status data in real time, and quantize the analog signal into a digital signal with 16-bit precision through a built-in ADC converter; a carrier communication module, connected to the data acquisition module, is used to encapsulate the quantized digital signal into a data frame, add a device ID, a timestamp and a CRC check code to the frame header, load it to the power line through orthogonal frequency division multiplexing modulation technology, and inject it into the power line through a coupling capacitor for transmission to a monitoring center; an intelligent analysis module, which is located in the monitoring center, is used to verify and analyze the received data frame, perform noise removal and outlier removal, and synchronously calculate time-frequency domain features such as current harmonic distortion rate and vibration spectrum entropy, input the pre-trained LSTM-Attention hybrid model output setting Standby status scoring; dynamic alarm module, connected to the intelligent analysis module, is used to dynamically adjust the abnormality threshold according to the equipment type and environmental parameters. When the score exceeds the threshold, an alarm information package containing the equipment ID, GPS coordinates, abnormality type code, score deviation value and timestamp is generated, triggering a multi-level alarm mechanism; closed-loop operation and maintenance module is used to push alarm information to the operation and maintenance terminal through the MQTT protocol, locate the abnormal point in the terminal's three-dimensional topology map and automatically generate a work order, assign it to the nearest operation and maintenance personnel, update the equipment health file after receiving feedback on the completion of maintenance, and terminate the alarm status. The existing power lines of the photovoltaic power station are used to transmit data, saving the cost of dedicated communication wiring. The modular architecture supports seamless expansion from distributed household power stations to 100-megawatt power stations. The closed-loop operation and maintenance system shortens the average fault repair time and reduces power generation losses. The combination of the three-level alarm mechanism and blockchain evidence storage not only meets the requirements of security and compliance audits, but also extends the life of equipment through preventive maintenance, and comprehensively reduces the operation and maintenance costs of the power station throughout its life cycle.

[0027] In this embodiment, the carrier communication module includes: a signal encapsulation unit, which is used to encapsulate the 16-bit digital signal into a data frame with a fixed length of 256 bytes, write the device ID and μs-level timestamp into the frame header, and append a double CRC check code to the frame tail; an anti-interference transmission unit, which uses 512-subcarrier OFDM modulation technology, inserts a cyclic prefix to suppress multipath effects, and injects it into the DC bus of the combiner box through a π-type filter coupling circuit; Signal enhancement unit, deploying gain-adjustable relay amplifiers at power line branch nodes, combining DPSK modulation with forward error correction coding to control the bit error rate to 10 -9 Next, carrier communication technology is used to achieve millisecond-level real-time monitoring of equipment operating status. Combined with a multi-dimensional sensor network, such as temperature, current, vibration, and environmental parameters such as light and humidity, the fusion analysis significantly improves the accuracy of fault identification.

[0028] This technical solution's optimized OFDM modulation with 512 subcarriers / 1-30MHz frequency band and π-type filter coupling design ensures communication reliability, enabling stable transmission even in strong electromagnetic interference environments. The dynamic threshold mechanism effectively reduces the false alarm rate by more than 40%, enabling a transition from passive response to predictive maintenance.

[0029] In this embodiment, the entire operation process can be controlled by a computer to provide signal feedback to implement the steps in sequence. These are all conventional knowledge of current automated control and will not be described in detail in this embodiment.

[0030] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for transmitting data via carrier wave in a real-time monitoring system of a photovoltaic power station, characterized in that: The specific steps include: S101: Deploy sensor networks on key equipment in a PV power plant, including PV panels, inverters, combiner boxes, and transformers, to collect real-time data on equipment operating status. The analog signals are converted into digital signals with 16-bit precision using ADC converters. S102: Encapsulate the quantized 16-bit precision digital signal into a data frame, add the device ID, timestamp and CRC checksum to the data frame header, load it onto the power line through carrier communication, and inject it into the power line through the coupling capacitor for transmission to the monitoring center; S103: The monitoring center verifies and analyzes the received data frames, removes transient noise, removes outliers using the Laida criterion, and simultaneously calculates and extracts the time-frequency domain features of the data frames. The features are then input into a pre-trained LSTM-Attention hybrid model to output a device status scoring standard. S104: The monitoring center dynamically adjusts the abnormality threshold based on the device type and environmental parameters. If the score exceeds the threshold, it is considered abnormal and generates an alarm information package. The alarm information package contains the device ID, GPS coordinates, abnormality type code, score deviation value and timestamp, realizing the triggering of a multi-level alarm mechanism; S105: Alarm information is pushed to the operation and maintenance terminal via the MQTT protocol. The operation and maintenance terminal displays the 3D topology of the equipment and locates the abnormal point. A work order is generated simultaneously and assigned to the nearest operation and maintenance personnel. After the maintenance is completed, the operation and maintenance personnel feedback the processing results to the monitoring center. The monitoring center updates the equipment health file and feedbacks to the multi-level alarm mechanism to stop the alarm.

2. The method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 1, wherein: In S101, a sensor network is deployed on key equipment in the PV power station, including PV panels, inverters, combiner boxes, and transformers, to collect real-time equipment operating status data, including: The sensor network deployment includes: deploying thin-film temperature sensors on the backplane of photovoltaic modules, installing PT100 platinum resistors on the inverter heat sink, integrating Hall-effect closed-loop current sensors on the combiner box bus, and fixing MEMS vibration sensors on the transformer body. The sensor network covers the head and tail nodes of each module string, the inverter IGBT module, and the transformer winding core. The operating status data of the photovoltaic modules, inverters, combiner boxes and transformers of the photovoltaic power station include physical quantity data of temperature, current, voltage, power and vibration parameters, and the sampling frequency of the status data is not less than 10 Hz.

3. The method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 2, wherein: In S102, the quantized 16-bit precision digital signal is encapsulated into a data frame, and the device ID, timestamp and CRC check code are added to the data frame header, including: Orthogonal frequency division multiplexing (OFDM) modulation is used to divide the 1–30 MHz frequency band into 512 subcarriers. A cyclic prefix is ​​used to eliminate multipath interference. The frame header contains the device ID, high-precision timestamp, and transmission sequence number. The data area is divided into independent fields for temperature, current, and voltage parameters. A double CRC checksum is appended to the end of the frame. The frame length is fixed at 256 bytes, and the insufficient part is padded with random numbers to ensure the bandwidth utilization during power line transmission; Subcarriers are allocated at equal intervals in the 1-30MHz frequency band with a subcarrier spacing of 58.6kHz. A cyclic prefix is ​​inserted to suppress the multipath effect, and the modulated signal is injected into the power line through a π-type filter coupling circuit.

4. A method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 3, characterized in that: Subcarriers are allocated at equal intervals in the 1-30 MHz frequency band, with a subcarrier spacing of 58.6 kHz. A cyclic prefix is ​​inserted to suppress multipath effects, and the modulated signal is injected into the power line through a π-type filter coupling circuit, including: The 1-30 MHz frequency band is divided into 512 equally spaced subcarriers, with guard bands reserved at both ends to avoid grid harmonic interference. Each subcarrier is modulated using QPSK, and a time-domain signal is generated through IFFT transform. A cyclic prefix is ​​inserted to cover the maximum multipath delay of the power line. Subcarrier power is dynamically allocated based on channel detection results. The optimized π-type filter coupling circuit, while meeting the requirements of 1-30MHz passband, less than 0.8dB insertion loss and 2kV high-voltage isolation, combines GDT surge protection with Smith chart impedance matching to efficiently inject the modulated signal into the combiner box DC bus.

5. The method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 4, wherein: In S103, the monitoring center verifies and analyzes the received data frame, removes transient noise, removes outliers using the Laida criterion, and simultaneously calculates and extracts the time-frequency domain features of the data frame. The features are then input into the pre-trained LSTM-Attention hybrid model, including: The monitoring center verifies and analyzes the received data frames and performs three-level processing: Data cleaning: Use sliding window filtering to remove transient noise and outliers. The window size must be more than 50 samples. Feature extraction, calculation of time-frequency domain features of current harmonic distortion rate, temperature gradient change rate, and vibration spectrum entropy; Anomaly detection is based on extracting calculated time-frequency domain features, inputting them into a pre-trained LSTM-Attention hybrid model for identification and judgment, and outputting a device status score. If the score exceeds a threshold, an anomaly is determined.

6. A method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 5, characterized in that: In S104, the monitoring center dynamically adjusts the abnormality threshold according to the device type and environmental parameters. If the score exceeds the threshold, it is determined to be abnormal and an alarm information package is generated, including: Based on the preset basic threshold of the device type and the dynamic correction of real-time environmental parameters, the temperature threshold is calculated according to the formula: T adj =T base +k1·GHI-k2·RH; Where GHI is light intensity, RH is humidity, k1 = 0.02°C·m² / Wk, and k2 = 0.5°C / %. The vibration threshold is dynamically generated by linking wind speed data with a Weibull distribution model. The threshold is refreshed within a preset time and the device status score is verified to be exceeded. When the status score exceeds the dynamic threshold, a binary alarm package is automatically generated. The alarm package triggers a three-level alarm based on the deviation value. The first alarm is pushed immediately, and the continuous abnormality is pushed to 2 n Retransmit at intervals of seconds, where n is the number of cycles during which the anomaly persists.

7. A method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 6, characterized in that: When the status score exceeds the dynamic threshold, a binary alarm package is automatically generated. The alarm package triggers three levels of alarms based on the deviation value, including: Automatic grading is performed based on the obtained score deviation value ΔS = |actual score - dynamic threshold| / threshold. When ΔS is less than 20%, a level 1 alarm is triggered, which sends a text message to the operation and maintenance team leader. 20%≤ΔS<50% triggers a level 2 alarm, which is reported to the responsible team via an app pop-up window and voice broadcast. ΔS≥50% or involves core equipment triggers a level 3 alarm, which triggers an emergency shutdown protection of the SCADA system and is simultaneously pushed to the large screen of the power plant control center. The first-level alarm sends the device ID + abnormal code through the operator's SMS gateway. The second-level alarm is pushed to the mobile terminal via the MQTT protocol, triggering a strong vibration reminder. The third-level alarm uses hard wiring + ModbusTCP dual channels to transmit to SCADA and execute the preset protection logic. All alarm logs are stored in the blockchain evidence library in real time and can be traced.

8. The method for transmitting data via carrier wave in a real-time monitoring system for a photovoltaic power station according to claim 7, wherein: In S105, after the maintenance is completed, the operation and maintenance personnel feedback the processing results to the monitoring center. The monitoring center updates the equipment health file and feedbacks to the multi-level alarm mechanism to stop the alarm, including: Operation and maintenance personnel use a mobile terminal app to scan the device's QR code and submit a maintenance report, including the cause of the fault, treatment measures, replacement part serial number, and processing time. After automatically verifying the data integrity, it is encrypted and transmitted to the monitoring center, triggering the electronic work order closed-loop process and simultaneously terminating the device's alarm status. The monitoring center analyzes fault handling records provided by operations and maintenance personnel, automatically calculates the mean-to-tr (MTTR) and fault level, and activates a threshold adaptive mechanism. Based on the historical number of faults and the temperature distribution curve, the center lowers the baseline temperature threshold using a step-by-step algorithm. Effective features are simultaneously extracted as input to the predictive maintenance model, generating a unique health baseline for the equipment. The updated health index is synchronized to the alarm module, SCADA system and mobile terminal in real time. When the health index is lower than the preset safety value, a preventive maintenance work order is automatically generated and assigned to the responsible person according to the team load balancing algorithm, and a spare parts inventory warning is triggered simultaneously.

9. A system for carrier wave data transmission in a real-time monitoring system of a photovoltaic power station, characterized in that: The method for transmitting data via a carrier wave of a real-time monitoring system according to any one of claims 1 to 8 is configured to include: The data acquisition module is deployed on key equipment such as photovoltaic panels, inverters, combiner boxes, and transformers. It is used to collect equipment operating status data in real time and quantize analog signals into 16-bit digital signals through the built-in ADC converter. The carrier communication module is connected to the data acquisition module and is used to encapsulate the quantized digital signal into a data frame, add the device ID, timestamp and CRC check code to the frame header, load it into the power line through orthogonal frequency division multiplexing modulation technology, and inject it into the power line through the coupling capacitor for transmission to the monitoring center; The intelligent analysis module, located in the monitoring center, verifies and analyzes received data frames, performs noise removal and outlier removal, and simultaneously calculates time-frequency domain features such as current harmonic distortion and vibration spectrum entropy. It then inputs the pre-trained LSTM-Attention hybrid model to output a device status score. The dynamic alarm module, connected to the intelligent analysis module, is used to dynamically adjust the anomaly threshold based on the device type and environmental parameters. When the score exceeds the threshold, an alarm information package containing the device ID, GPS coordinates, anomaly type code, score deviation value and timestamp is generated, triggering a multi-level alarm mechanism; The closed-loop operation and maintenance module is used to push alarm information to the operation and maintenance terminal through the MQTT protocol, locate abnormal points in the terminal's three-dimensional topology map, automatically generate work orders, and assign them to the nearest operation and maintenance personnel. After receiving feedback on maintenance completion, the device health file is updated and the alarm status is terminated.

10. A method and system for carrier wave data transmission in a photovoltaic power station real-time monitoring system according to claim 9, characterized in that: The carrier communication module includes: The signal encapsulation unit is used to encapsulate the 16-bit digital signal into a data frame with a fixed length of 256 bytes. The device ID and μs-level timestamp are written into the frame header, and a double CRC check code is appended to the frame tail. The anti-interference transmission unit adopts 512-subcarrier OFDM modulation technology, inserts a cyclic prefix to suppress multipath effects, and injects it into the combiner box DC bus through a π-type filter coupling circuit; Signal enhancement unit, deploying gain-adjustable relay amplifiers at power line branch nodes, combining DPSK modulation with forward error correction coding to control the bit error rate to 10 -9 the following.

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